Business objects PERFORMANCE MANAGER XI 3.0 User Manual

BusinessObjects Performance Manager XI 3.1 Administrator's Guide

BusinessObjects Performance Manager XI 3.1

windows

© 2008 Business Objects, an SAP company. All rights reserved. Business Objects owns the following U.S. patents, which may cover products that are offered and licensed by Business Objects: 5,295,243; 5,339,390; 5,555,403; 5,590,250; 5,619,632; 5,632,009; 5,857,205; 5,880,742; 5,883,635; 6,085,202; 6,108,698; 6,247,008; 6,289,352; 6,300,957; 6,377,259; 6,490,593; 6,578,027; 6,581,068; 6,628,312; 6,654,761; 6,768,986; 6,772,409; 6,831,668; 6,882,998; 6,892,189; 6,901,555; 7,089,238; 7,107,266; 7,139,766; 7,178,099; 7,181,435; 7,181,440; 7,194,465; 7,222,130; 7,299,419; 7,320,122 and 7,356,779. Business Objects and its logos, BusinessObjects, Business Objects Crystal Vision, Business Process On Demand, BusinessQuery, Cartesis, Crystal Analysis, Crystal Applications, Crystal Decisions, Crystal Enterprise, Crystal Insider, Crystal Reports, Crystal Vision, Desktop Intelligence, Inxight and its logos , LinguistX, Star Tree, Table Lens, ThingFinder, Timewall, Let There Be Light, Metify, NSite, Rapid Marts, RapidMarts, the Spectrum Design, Web Intelligence, Workmail and Xcelsius are trademarks or registered trademarks in the United States and/or other countries of Business Objects and/or affiliated companies. SAP is the trademark or registered trademark of SAP AG in Germany and in several other countries. All other names mentioned herein may be trademarks of their respective owners.

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Business Objects products in this release may contain redistributions of software licensed from third-party contributors. Some of these individual components may also be available under alternative licenses. A partial listing of third-party contributors that have requested or permitted acknowledgments, as well as required notices, can be found at: http://www.businessobjects.com/thirdparty

2008-09-03

Audience 7Chapter 1

Performance Manager Administrator's Guide 9Chapter 2

High-level overview....................................................................................10

Database configuration and tuning............................................................10

Dashboard and Analytics repository..........................................................11

Metric domain (CI_ prefix).........................................................................11

Performance Manager domain (IPM_ prefix)............................................12

Set Domain (SET_ prefix)..........................................................................12

Standard options for servers......................................................................13

Changing the services startup parameters on UNIX.................................17

Metric Universes........................................................................................18

Universe overview................................................................................18

Metric universe overview......................................................................18

Multiple metric universes......................................................................19

Creating a Basic Enterprise Metric.......................................................19

Set-based Metrics................................................................................26

Advanced Topics..................................................................................42

Configuring universes for process control charts.................................44

Performance Manager Setup and Administration Online Help 51Chapter 3

Dashboard and analytic applications.........................................................52

What is Dashboard Builder?.................................................................52

What is Performance Manager?...........................................................52

What is Predictive Analysis?................................................................52

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 3

Contents

What is Process Analysis?...................................................................53

What is Set Analysis?...........................................................................53

Deployment of Dashboard and Analytics tools to your organization.........53

Performance Manager servers..................................................................55

Performance Manager server options..................................................56

Dashboard and Analytics launch errors...............................................63

The Performance Manager repository.......................................................65

Overview of the Dashboard and Analytics deployment........................65

Creating the Performance Manager repository....................................67

Central Management Server authentication.........................................70

Performance Manager repository migration.........................................71

Performance Manager repository integrity and cleanup......................72

Dashboard and Analytics system users....................................................77

Metric universes.........................................................................................79

About metric universes.........................................................................80

Building metric universes.....................................................................81

Making metric universes available to Dashboard and Analytics users.81

Defining connections for universes......................................................81

Updating a universe in Dashboard and Analytics Setup......................83

Object metadata in universes...............................................................84

External metric refresh.........................................................................86

Sliced metric dimensions...........................................................................88

What are dimensions and sliced metrics?............................................88

Where are dimensions defined?..........................................................89

Sliced metrics.......................................................................................97

Analytics calendars....................................................................................97

Calendar properties..............................................................................98

Moving averages in calendars...........................................................105

Difference calculations in calendars...................................................110

Rollups in calendars...........................................................................113

Rules templates.......................................................................................115

4 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

Contents

About rules and rules templates.........................................................115

Creating and editing rules templates..................................................118

Universe value list templates...................................................................121

Application activity tracing.......................................................................125

Individual Profiler portrait properties........................................................127

Analytic Template Publisher.....................................................................129

Installing the XCTemplateUploader.war File......................................130

Deploying the Crystal Xcelsius templates..........................................130

Publishing a new Crystal Xcelsius template.......................................131

Publishing a Crystal Xcelsius template archive..................................132

Downloading a Crystal Xcelsius template..........................................133

Working with the template properties file...........................................133

Data sources accepted by the Crystal Xcelsius data model..............137

Modifying the XLF file after the template has been published...........137

Modifying the XLS file after the template has been published...........138

Process Analysis control charts setup.....................................................138

Control chart samplings......................................................................138

Control chart filters.............................................................................141

Control chart alarms...........................................................................143

Terms and concepts.................................................................................145

Aggregation functions.........................................................................145

What is an analytic?...........................................................................151

What is binning?.................................................................................151

What is a control chart?......................................................................151

What is differencing?..........................................................................152

What is a dimension?.........................................................................152

What is a grain?.................................................................................152

What is a metric?................................................................................153

Moving averages explained...............................................................153

What is a sliced metric?.....................................................................157

What is a variable?.............................................................................157

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 5

Contents

Get More Help 159Appendix A

Index 163

6 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

Audience

This guide is for administrators of BusinessObjects Performance Manager.

The first section of this guide contains information on creating metric universes used to build analytics in Performance Manager.

The second section of the guide contains a printable version of the Performance Manager Setup and Administration Online Help for your convenience.

For detailed information on installation and deployment of BusinessObjects XI 3.0 refer to the following:

•

BusinessObjects Enterprise XI 3.0 Installation and Configuration Guide for Windows

•

BusinessObjects Enterprise Deployment Planning Guide

8 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

Performance Manager Administrator's Guide

High-level overview

As an administrator of the performance management products you need to be familiar with of BusinessObjectsInfoView and with Designer.

For information on configuring the Dashboards and Analytics framework refer to the Setup and Administration help that is available from the Setup page. This help covers a number of important topics including:

• Connecting to the dashboards and analytics repository

• Connecting to the universe

• Setting up calendars

Business Objects recommends that you have the guides listed below ready for reference.

•

BusinessObjects XI 3.0 Administrator's Guide - provides information and procedures covering a wide range of administrative tasks.

•

Designer's Guide - provides complete information on how to use Designer to design, create, and manage Business Objects universes.

•

BusinessObjects XI 3.0 Installation Guide - guide provides information and procedures for installing BusinessObjects, and includes detailed instructions for the different installation modes available.

Database configuration and tuning

Although optimization of the Dashboard and Analytics repository leads to performance gains, the typical deployment gains the most from a well set-up source database.

A time period is one of the key factors in limiting queries in most deployments that involve sets and metrics. Therefore, it is essential to consider the type of SQL used in queries and key date fields.

Business Objects recommends using BusinessObjects or Web Intelligence directly against the metric universe to generate a test SQL statement that would be a typical metric. This SQL can then be tested and traced to check that indexes are in place and are being used.

10 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

Performance Manager Administrator's Guide

Dashboard and Analytics repository

The Dashboard and Analytics repository is split into three domains or sets of tables that are created when you deploy a new PM repository.

• Metric domain: Dashboard Builder tables in which metrics, rules and other

Dashboard and Analytics information is stored. The table names have a

CI_ prefix, for example, CI_PROBE_VALUE.

• Performance Manager domain: Performance Manager tables in which

goals and target values are stored. These contain all the data required by Performance Manager such as goals and target values, as well as strategies and roles. The table names have an ipm_ prefix, for example,

ipm_analytic.

• Set domain: Set Analyzer tables in which sets are stored for the

segmentation engine. These are the tables required to store the Set Analyzer data. The table names have a SET_ prefix, for example,

SET_SET_DETAIL.

Metric domain (CI_ prefix)

The Metric domain (CI_ prefix) can initially be sized as the Universe domain. In this case, the number of universes in the table corresponds to the number of universes pushed in the Dashboard and Analytics setup page. These universes are stored in tables in the metric domain as the basis for metric creation.

CI_PROBE_VALUE

As with the set domain you can use a simple calculation to determine storage size using the CI_PROBE_VALUE table for the metric values as follows:

Number of metrics * number of periods of history

Further storage may be required for dimensioning, so consider modifying this calculation as follows:

Number of metrics * number of periods of history * number of distinct dimension values

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 11

Performance Manager Administrator's Guide

Performance Manager domain (IPM_ prefix)

CI_TARGET_VALUE

If you are using Performance Manager the CI_TARGET_VALUE table can also be of significant size. You can estimate the size as follows:

number of goals * number of periods

If you are using dimensions, the calculation is:

number of goals * number of periods * number of distinct dimensions

CI_PROBE_VALUE

The metric domain can also be set up to allow separate table spaces for the

CI_PROBE_VALUE table, which typically grows quite large compared with the

other CI_ tables.

Performance Manager domain (IPM_ prefix)

The size of the Performance Manager domain is a simple calculation based on the number of roles, actions, and other values that can be used.

Set Domain (SET_ prefix)

The set domain contains all set metadata, including the security and special-set user information. Start with an initial size based on the number of users. Business Objects recommends allocating 1/2MB per user.

If you plan to use sets in your deployment you must consider the storage requirement for set membership by answering the following questions:

• What type of sets will be used?

• What is the size of the sets?

• If the sets are dynamic, what are the history requirements and what

turnover is expected?

The following example shows how you can easily estimate the size of the Set domain of the Dashboard and Analytics repository by creating a test table.

12 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

Performance Manager Administrator's Guide

Standard options for servers

You estimate:

• the number of rows

• the size of a row

Example:

100 dynamic sets, an average of 100,000 members, keeping 12 months of history, with, on average, 25% turnover

100 * (100,000 + (12*(25,000))) = 40 million rows

A row in SET_SET_DETAIL (or SET_SET_DETAILC if using a character key) consists of the following table structure:

SetID number(), ID number(), Points number(), Sdate date(), Edate date()

The set domain performance is greatly influenced by the SET_SET_DETAIL tables. For optimal results in a deployment in which sets are used, Business Objects recommends:

•

allocating specific table space for the SET_SET_DETAIL table and its index

•

using setup options such as table partitioning to greatly improve performance

•

carrying out regular index analysis since table style and size can change

Set Analyzer also allows you to set parallel query options that improve performance, if the database used to host the repository supports this.

Standard options for servers

These command-line options apply to all of the BusinessObjects Enterprise servers, unless otherwise indicated.

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 13

Performance Manager Administrator's Guide

Standard options for servers

-name

string

BehaviorValid ArgumentsOption

Specify the friendly name of the server.

The server registers this name with the Central Management Server (CMS), and the name is displayed in the CMC. The default friendly name is hostname.servertype

Note:

• Do not modify -name for a CMS.

• If you modify -name for an Input or Output File Repository Server, you must include "Input." or "Output." as the prefix to the value you type for string, for example,

-name Input.Server01

-name Output.UK.

Specify the CMS with which the server should register. Add the port if

-ns

14 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

cmsname [:port]

the CMS is not listening on the default (6400). This option does not apply to the CMS itself.

Performance Manager Administrator's Guide

Standard options for servers

BehaviorValid ArgumentsOption

Specify the port on which the server listens. The server registers this port with the CMS. If unspecified, the server chooses any free port >

1024.

-requestPort

-port

port

[interface:]

[port]

Note: This port is used for different purposes by different servers. Before changing, see the section on Changing the default server port numbers" in the BusinessObjects XI Release 2 Administrator's Guide.

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 15

Performance Manager Administrator's Guide

Standard options for servers

BehaviorValid ArgumentsOption

Binds WCA or CMS to the specified port , or to the specified network interface and port. BInds other servers to the specified network interface. Useful on multihomed machines or in certain NAT firewall environments.

•

Use -portport or

-portinter

face:port for WCA and CMS.

•

Use -port inter facefor other servers. The port command is used for different purposes by different servers. Before changing, see Changing the default server port numbers " in the BusinessOb-

jects Enterprise XI Release 2 Administrator's Guide.

•

16 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

If you change the default port value for the CMS, you must perform additional system configuration. For more information see Changing the default server port numbers "in the

Performance Manager Administrator's Guide

Changing the services startup parameters on UNIX

BehaviorValid ArgumentsOption

BusinessObjects Enterprise XI Release 2 Administrator's Guide

Server restarts if it exits

-restart

with an unusual exit code.

Changing the services startup parameters on UNIX

If you want to change the services startup parameters on UNIX for example, in the case of a DMZ deployment, you must:

1. Manually edit the INSTALLDIR/bobje/ccm.config file to add or change

the parameters values.

2. Restart the services.

Changing the services startup parameters on UNIX

If you want to change the services startup parameters on UNIX for example, in the case of a DMZ deployment, you must:

1. Manually edit the INSTALLDIR/bobje/ccm.config file to add or change

the parameters values.

2. Restart the services.

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 17

Performance Manager Administrator's Guide

Metric Universes

Universe overview

A universe is used to represent the underlying data schema used with the performance management products, allowing a visual view of what can lead to complex SQL generation. You use Designer to build universes that specify the SQL used to define metrics. You then usePerformance Manager to create analytics that use metrics to track performance.

For detailed information on how to design, create, and manage BusinessObjects universes refer to the Designer's Guide .

Metric universe overview

Metrics are time-based aggregate values based on sets, set behavior, or filters. A metric is composed of the following:

ExampleMetric component

Measure object

Date-based self-join or where clause

Set or data based filter

The process of creating a metric universe is comprised of the following stages that are described in more detail:

• Creating the universe on a target fact table.

18 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

SUM(SALES)

DATEFIELD between START and END

•

Set based: SETSTARTDATE = START, for example, Joiners

•

Data based: COUNTRY = 'Eng land'

• Creating measures, with filters and date restrictions

• Making the universe available to Performance Manager

• Creating the metric in Performance Manager

For in-depth information on creating universes, and specifically, on creating measures, refer to the Designer's Guide.

Multiple metric universes

The dashboards and analytics framework supports the ability to build metrics from multiple universes. This simplifies a system universe by breaking down the universe structure and creating a new universe for specific subject areas.

For enterprise metrics, multiple universes can be used to select from multiple data sources.

In the diagram below subject areas 1 and 2 are defined as enterprise metrics, and subject areas 3 and 4 as set-based metrics. The results of metric calculations on connections 1 and 2 are written into the dashboard and analytics repository tables that are located in the same schema as Set Analyzer , which is Connection 3 in the diagram below.

Performance Manager Administrator's Guide

Metric Universes

Creating a Basic Enterprise Metric

Enterprise metrics

An enterprise metric is a metric that contains a date-based filter defined on the entire population of entities limited by a simple

WHERE restriction, for example,

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 19

Performance Manager Administrator's Guide

Metric Universes

COUNTRY=England

An enterprise metric is calculated at a non-set level, that is, without using the set metadata tables

Creating the universe on a target fact table

A fact table is the starting point in creating metrics. In Designer you create a universe based on the fact table and define a connection to the source database. You then load the table into the structure pane. You create classes to organize the measures into groups. You then use this universe in Performance Manager to create metrics from the measures.

The following image shows a sample sales table that is used to create the measures that are the basis of the metrics. The table contains a date field, which is an important element for time-based metrics.

Creating a measure

To define the value for the basis of the metric calculation, in you need to create a measure object using a field from the fact table. This example uses the values in the sales_actual column from the sales table.

The select statement for the object, unlike that of an object in a typical universe, does not contain an aggregate function, that is, sum, max, min, avg, because you select the type of aggregate when you define the metric.

Creating a measure object

In Designer:

1. Using the "sales_actual " field from the Sales table, create an object.

2. Under the Properties tab, change the object qualification to Measure .

20 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

The SQL generated reads:

SELECT agrfunc (SALES_ACTUAL)FROM SALES

Definition of a filter

The final element of this enterprise metric universe is the population restriction, or filter. You use these filters in Performance Manager to limit metrics when you create them.

In this example we use the filter that is used does not limit the query at all, which means that the query returns a total of sales on a period by period basis for all orders in the fact table, Sales. The SQL behind the restriction in this case is simply a true statement and does not limit the scope of the query.

Defining a filter

In Designer in the "Object Properties " dialog box, click the Properties tab.

1. In Designer in the "Object Properties " dialog box, click the Properties

tab.

2. Modify the object's qualification to Measure .

The SQL reads as follows:

SELECT agrfun(SALES_ACTUAL)FROM SALES WHERE sales.start_date

between @PROMPT ('BEGIN_DATE','D',,mono,free) AND @PROMPT

('END_DATE','D','D',,mono,free) AND 1=1

Performance Manager Administrator's Guide

Metric Universes

Exporting the universe

Once you have created and saved the metric universe, you need to make it visible to Performance Manager to used as the basis for metric creation. In Designer, you create a connection for the metadata, then export the universe to the dashboard and analytics metadata tables.

Before you begin creating metrics in Performance Manager you add this universe to the list of available universes from the "Universes " page in the Dashboard and Analytics System Setup.

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 21

Performance Manager Administrator's Guide

Metric Universes

Dimension table filters

When you create filter objects you are not restricted to using the fact table on which the metric is based. You can also use other lookup/dimension tables.

When you modify a universe by building filters on other tables, you need to update Dashboard and Analytics metadata with the new structure and objects. You do this from the Universes page in the Dashboard and Analytics System Setup by selecting the saved universe and clicking Update. The changes and new objects are then visible for metric creation.

In the example of a filter created against a dimension table, the metric SQL generated is:

SELECT agrfunc(SALES_ACTUAL) FROM SALES, PRODUCT WHERE sales.start_date between @Prompt('BEGIN_DATE','D',,mono,free) AND @Prompt('END_DATE','D',,mono,free) AND SALES.PRODUCT_ID = PRODUCT.PRODUCT_ID AND PRODUCT.DESCRIPTION='Motorola Timeport'

Refer to the Dashboards and Analytics online help for information on updating metrics with changes in target universes.

Pre-selecting aggregate functions and measure parameter passing

You may not want users to be able to set aggregate functions or perhaps using aggregate functions is not possible, for example, in calculating an average, as in the following SQL statement:

Sum(sales.sales)/sum(sales.volume)

In either case, you need to pre-set aggregate functions.

In the above example, if an aggregate such as sum is wrapped around the SQL, it is invalid. If, for a particular period, there is no volume, the SQL generates a divide-by-0 error.

You need to create an Average Sales object in Designer and then edit the definition of the object in the"Edit Properties" dialog box.

22 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

In this case you create an Average Sales object and the enter the following under "Description".

AGGR=SUM;DESC=Calculates average sales and avoids divide by zero errors.

The statement says that the aggregate is already chosen and it is a sum. It also passes in a description - note that parameters are delimited with a semi-colon.

Under"Select" you enter the folllowing:

decode(sum(sales volume),0,0,sum.sales_actual/sum(slaes.volume))

When you look at the universe content in Performance Manager you see that Aggregation has been pre-set and it cannot be modified.

Complexities of the self-join

A self-join is used in any generated SQL that involves the table with the self-join. Using the self-join, however, may not always lead to the desired results. For example, if you want to calculate a rolling value for the volume over the past three months, the date restriction needs to take into account the past three months rather than the fixed one-month, if a monthly calendar is used.

Performance Manager Administrator's Guide

Metric Universes

To achieve the desired result you can use one of two methods that are explained in the following examples:

Example: You replace the self-join with an object-based WHERE clause.

In Designer in the Edit Properties dialog box:

In the Select box type: sales.sales_actual

In the Where box type: sales.start_date between @Prompt('BE

GIN_DATE','D',,mono,free) AND

@Prompt('END_DATE','D',,mono,free)

Example: You modify the date restriction to change the period of

observation.

In the Select box type: sales.volume

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 23

Performance Manager Administrator's Guide

Metric Universes

In the Where box type: sales.start_date between month

add(@Prompt('BEGIN_DATE','D',,mono,free),-2) AND

@Prompt('END_DATE','D',,mono,free)

Date lookups

Period tables are often included in data warehouses, and are often required in metric calculation because they contain time-related information.

A common fact table may not always contain true date fields, but may instead contain date/period ids that provide the foreign key to a period/date dimension table.

The figure below shows how the system universe can be made to accommodate such a schema. Note the self-join, placed against the real (actual) date field in the period table, or date table, in this example.

You need to force performance manager to use the period table, in this case the dates table, when generating metric SQL. The simplest way to do this is to modify the tables associated with the measure objects to force use of the date table hence forcing use of the self-join as shown as follows:

SELECT agrfunc(SALES2.SALES_ACTUAL) FROM SALES, DATES WHERE SALES2.DATE_ID = DATE.DATE_ID) AND DATES.ACTUALDATE between @Prompt('BE GIN_DATE','D',,mono,free) AND @Prompt('END_DATE','D',,mono,free) AND SALES2.DATA_ID = DATES.DATE_ID

24 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

Tip:

Where there is no date field in your table (no ID) but there is a simplified date such as a year field or a year + month field, you can use the following syntax to transform the dates.

Example: For Oracle:

SELECT... FROM... WHERE... yyyy between @Prompt (to_char ('BEGIN_DATE','yyyy')

Example: For SQL Server and DB2

SELECT... FROM... WHERE... yyyy between @Prompt (year ('BEGIN_DATE'),...)

Dimensions and slicing metrics

The principle of slicing or dimensioning a metric is to take a metric value, for example, Sales Actual, and break it down by a dimension object, for example by promotion, by country, or by category. At the SQL level this means employing a GROUP BY clause.

Performance Manager Administrator's Guide

Metric Universes

The example below shows a dimension, Promo Description. Information about the promotion name is stored in the promotion table, therefore, this table is added to the universe and joined to the fact table (sales) on promo

tion_type.

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 25

Performance Manager Administrator's Guide

Metric Universes

Standard dimension objects are then created for promotion_id and pro

mo_description from the "System Setup"against the dimension table. You

add a Global Slice Name in the "Dimension Creation" dialog box. You can place restrictions on users to allow them to see only specific values.

You then select a measure, an aggregation function, and a dimension to create a metric. You use these metrics to in Performance Manager to create an Interactive Metric Trend analytic. The Interactive Metric Trend, which is a visual representation of the data.

A link appears below the legend that allows the values in the chart to be sliced. When selected, the Sales Actual value is split into the distinct available values for promotion. The figure below is an example of a sliced metric.

Sliced metrics can be displayed well in Kiviat and radar diagrams.

Set-based Metrics

Set-based metrics

A set-based metric is a metric that contains a filter defined on a set, or the behavior in a set, for example, Joiners of the Gold Set. This type of metric is set to automatically refresh with the set at fixed processing time, rather than an independent refresh.

26 BusinessObjects Performance Manager XI 3.1 Administrator's Guide

Performance Manager Administrator's Guide

Design principles and SET_SET_DETAIL[C/D]

When a set is built, the set information is saved in one of the tables shown below.

The tables allow you to use different data types in set creation. If the set is a list of customers, where the customer_id is text-based, the set tables resemble the figure below.

Metric Universes

If customer_id is a character-based value, the set is stored in the SET_SET_DETAILC table where the ID field is character type. If you create a set of, for example, products where the Product_Key field is numeric, the SET_SET_DETAIL table can be used. This also holds true for date-based sets. If you create date-based segments the SET_SET_DETAILD table can be used in the same way.

The structure of this table allows Set Analyzer and the performance management framework to store membership details over time. Using this information you can section the set members/non-members into various sub-sets. The following is an example of a set of customers where the ID is the customer's name. As this is a character-based key you view SET_SET_DETAILC. The set is refreshed on a monthly basis starting on the 1st January 1999.

Example: Period 1

•

Joiners: Tom, Colin, Fran

•

Members: Tom, Colin, Fran

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 27

Performance Manager Administrator's Guide

Metric Universes

•

Stayers:

•

Leavers:

When first refreshed, the set contains one row per customer in the set. The SDATE value is set to the period time at which the set was refreshed. The EDATE value is set to a default date, which means that the customer has not yet left the set. This is a reserved date that implies an infinite date; in the case of Set Analyzer the date used is 1/1/2999.

At this point, the three entries represent three customers who have met the set criteria for the period and are therefore Members who are Joiners.

Example: Period 2

•

Joiners: Edd

•

Members: Edd, Tom, Colin

•

Stayers: Tom, Colin

•

Leavers: Fran

In period two, Fran has left the set. Set Analyzer updates the EDATE value with the current period date to represent this. Another customer, Edd, has joined the set. Tom and Colin are still members at this time so their records are not updated. They are Stayers.

Example: Period 3

•

Joiners: Fran

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Performance Manager Administrator's Guide

Metric Universes

•

Members: Fran, Edd, Tom, Colin

•

Stayers: Edd, Tom, Colin

•

Leavers:

Period three shows only one change. Fran, the leaver for the second period, has now met the criteria to be a set member again. Therefore a new row is entered with the SDATE value as his time of joining and again the EDATE value as the default for a member. He can now be classified as a re-joiner as there is historic information on his membership.

Example: Period 4

•

Joiners:

•

Members: Fran, Colin

•

Stayers: Fran, Colin

•

Leavers: Tom, Edd

Period 4 shows no new joiners, however, the EDATE values for Tom and Ed have been updated to the current period date. This means they have left the set, leaving Fran and Colin as stayers/members.

A static (non calendar-based) set does not store the history of a segment's membership over time. This lack of history means you are able to show the membership of the set and not be able to break this into segments.

BusinessObjects Performance Manager XI 3.1 Administrator's Guide 29

Performance Manager Administrator's Guide

Metric Universes

A static set does not store history over time. It is a fixed view of a certain period in time which explains why it is also known as a snap-shot. For example, such a set can show all the customers who purchased goods yesterday. This may change over time but information on who bought goods three days earlier is not stored.

A hybrid of this is a 'vintage set', which is a set that never changes membership, for example customers who purchased goods in January

1976. Therefore, unlike the time-based, dynamic segments, there are never

Joiners, Leavers, and so on. You need track only Members for metrics based on such segments. The figure below shows how snapshot/vintage sets are stored in the set membership tables.

The universe for set-based metrics is similar to an enterprise metric universe. The notable addition is the inclusion of SET_SET_DETAIL[C/D] in the schema.

As with an enterprise universe, you can use a self-join to limit the metric calculation to the period of metric observation. This can also be defined in the measure Where clause if required.

The method of passing values into prompts as used in the date restriction is also used to select the set against which the metric is to be calculated. The self-join syntax rules apply as with the date prompts, for example, a case-sensitive string match.

Creating set-based metrics

You create set-based metrics Performance Manager in the same manner in which you create enterprise metrics. With set-based metrics you have a choice of the sets and subsets on which you base the metrics.

For example, in the set Collector, a dynamic set with membership history, you can select behavioral subsets, such as Members, Joiners, Stayers, and Leavers.

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Using Filter objects in Set-based metrics

In a set-based universe, you use filter objects to define subsets such as Members, Joiners, and Leavers. You can copy them from the example universe since the syntax is Set Analyzer-specific and does not change. The figure below shows three separate classes. These class names directly relate to the subject area that holds the sets in Set Analyzer. The suffixes T and T2 denote the type of membership that can be monitored.

The members filter under Customer is used with non-dynamic, snapshot sets. No membership date restrictions are needed because if the customers are currently in the set they are entered in the set detail table. If they are not currently in the set they are not entered in the set details table. In this case, only a restriction on the set id is required. For example, "I want to have the metric value for all the people in the XXX set."

Defining members for a snapshot set

Name=Member

1. In the Description box type: FILTER=M

2. In the Where box type:

set_set_detail.setversion_id=@Prompt('SET_VER SION','N',,mono,free)

The filters under the Customer T class are used for dynamic sets with time-based history. The members definition illustrates use of begin date and

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end date prompts. In this case, the dates indicate whether the customer entered the set in the current period or an earlier one, and whether or not he left after the end date of the current period. These dates determine whether the customer is in the set during the observation period.

Defining membership for a time-based set

1. In the Description box type: FILTER=M

2. In the Where box type:

set_set_detail.sdate <=@Prompt('TSET_END_DATE','D',,mono,free) and set_set_detail.edat > @Prompt('TSET_END_DATE','D',,mono,free)

Once you have saved the universe you can make it available to the performance management framework as you would an enterprise universe.

Creating the universe for set-based metrics

The universe for set-based metrics is similar to enterprise metric universes. The notable addition is the inclusion in SET_SET_DETAIL[C/D] in the schema. The figure below shows a universe that incorporates set tables.

As with the enterprise universe, you can use a self-join to limit the metric calculation to the period of metric observation. The period of metric observation can also be defined in the measure WHERE clause if required.

The method of passing values into prompts as used in the date restriction is also used to select the set against which the metric is calculated. The following example shows the self-join syntax. The string match is case-sensitive.

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Example: Self-join

set_setdetail.setversion_id=@Prompt('SET_VER SION','N',mono,free)

The measure Sales Actual is defined for set-based metrics in the same way as for enterprise universe. However, a measure called count is introduced in the set -based universe. This example shows the measure definition of count. Note the aggregate is preselected and the count is of the unique id, in this example, customer_id.

Example: Membership count measure definition

In the Description box type: AGGR=SUM; COUNT=Y

In the Select box type: count(set_set_detail.id)

Using Filter objects in Set-based metrics

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Defining members for a snapshot set

Name=Member

1. In the Description box type: FILTER=M

2. In the Where box type:

set_set_detail.setversion_id=@Prompt('SET_VER SION','N',,mono,free)

The filters under the Customer T class are used for dynamic sets with time-based history. The members definition illustrates use of begin date and end date prompts. In this case, the dates indicate whether the customer entered the set in the current period or an earlier one, and whether or not he left after the end date of the current period. These dates determine whether the customer is in the set during the observation period.

Defining membership for a time-based set

1. In the Description box type: FILTER=M

2. In the Where box type:

set_set_detail.sdate <=@Prompt('TSET_END_DATE','D',,mono,free) and set_set_detail.edat > @Prompt('TSET_END_DATE','D',,mono,free)

Once you have saved the universe you can make it available to the performance management framework as you would an enterprise universe.

Insight into subsets

Below is the SQL for each of the four basic subset filters:

• Members

• Joiners

• Stayers

• Leavers

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In the case of Same-as-Set metrics,

TSET_END_DATE

and

TSET_BEGIN_DATE

contain the same values as the

BEGIN_DATE

and

END_DATE

prompts used in the joins described earlier. However, the nature of independent set-based metrics may mean that the dates passed to the set differ from those passed to the metric.

Below are descriptions of the filters in the Customer T section of the universe.

FILTER=M; DESC=Members at the end of the period

CI_TID_01.sdate <= @Prompt('TSET_END_DATE','D',,mono,free) and

CI_TID_01.edate > @Prompt('TSET_END_DATE','D',,mono,free)

Joiners

Stayers

Member (p) is a Member at the end of the period (p).

FILTER=J; DESC=Members at the end of the period that were not members at the end of the previous period

CI_TID_01 = @Prompt('TSET_BEGIN_DATE','D',,mono,free)

Joiner (p) is a member at the end of the period (p) that was not a member at the end of the previous period.

FILTER=S; DESC=Members at the end of the period that were members at the end of the previous period

CI_TID_01.sdate < @Prompt('TSET_BEGIN_DATE','D',,mono,free) and CI_TID_01.edate > @Prompt('TSET_END_DATE','D',,mono,free)

Stayer (p) is a member at the end of the period (p) that was a member at the end of the previous period.

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Leavers

FILTER=L; DESC=Non-members at the end of the period that were members at the end of the previous period

CI_TID_01.edate = @Prompt('TSET_BEGIN_DATE','D',,mono,free)

Leaver (p) is a Non Member at the end of the period (p) that was a member at the end of the previous period.

Example:

You can apply a quarterly metric to a segment that identifies monthly high revenue customers to show the total revenue for these customers. These are calculated using the filters in Customer T2.

Types of subsets

Below are the SQL definitions for each of the subset types followed by a description of what the SQL does.

Members

FILTER=M; DESC=Members at the end of the period

CI_TID_01.sdate <= @Prompt('TSET_END_DATE','D',,mono,free) and

CI_TID_01.edate > @Prompt('TSET_END_DATE','D',,mono,free)

In the scenario shown below the customer joined in p2 and left the segment at p9, and was definitely a member during the period of observation (p4, p5 and p6).

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Joiners

FILTER=J; DESC=Members at the end of the period that were not members at the end of the previous period

CI_TID_01.sdate <= @Prompt('TSET_END_DATE','D',,mono,free) and

CI_TID_01.edate > @Prompt('TSET_END_DATE','D',,mono,free) and

CI_TID_01.id not in ( select set_set_detail.id from set_set_detail where set_set_detail.sdate < @Prompt('TSET_BE GIN_DATE','D',,mono,free) and set_set_detail.edate >= @Prompt('TSET_BEGIN_DATE','D',,mono,free) and set_set_de tail.setversion_id = @Prompt('SET_VERSION','N',,mono,free) )

Joiners must:

• Not be present during the start of the period of observation.

• Be present at the end of the period of observation for the metric.

If both these criteria are met the customers are classified as joiners. In the diagram below, the period of observation starts at p4 and ends after p6. A joiner is, then, a customer who is not present in p3, but who is present at the end of p6.

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Stayers

FILTER=S; DESC=Members at the end of the period that were members at the end of the previous period

CI_TID_01.sdate <= @Prompt('TSET_END_DATE','D',,mono,free) and

CI_TID_01.edate > @Prompt('TSET_END_DATE','D',,mono,free) and CI_TID_01.id in ( select set_set_detail.id from set_set_detail

where set_set_detail.sdate < @Prompt('TSET_BE GIN_DATE','D',,mono,free) and set_set_detail.edate >= @Prompt('TSET_BEGIN_DATE','D',,mono,free) and set_set_de tail.setversion_id = @Prompt('SET_VERSION','N',,mono,free) )

To be classified as Stayers customers must be present at the start and at the end of the period of observation. In the diagram below, stayers are customers who are present at the start of p4 and at the end of p6.

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Leavers

FILTER=L; DESC=Non Members at the end of the period that were members at the end of the previous period

CI_TID_01.id not in ( select set_set_detail.id from set_set_detail where set_set_detail.sdate <= @Prompt('TSET_END_DATE','D',,mono,free) and set_set_detail.edate

> @Prompt('TSET_END_DATE','D',,mono,free) and set_set_de tail.setversion_id = @Prompt('SET_VERSION','N',,mono,free) ) and CI_TID_01.sdate < @Prompt('TSET_BEGIN_DATE','D',,mono,free)

and CI_TID_01.edate >= @Prompt('TSET_BE GIN_DATE','D',,mono,free)

Leavers are present at the start of the period of observation but not at the end. In the diagram below, leavers are present at the start of p4 and absent at the end of p6.

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Using multiple fact tables

Multiple fact tables are easily handled in the metric universe. The following figure shows the customer subject area extended to encompass the complaints fact table.

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As with the sales table, a self-join, or object WHERE clause is required to enforce period-by-period calculations. Measure objects that become the basis for metrics are also defined in the same way as the sales fact.

Multiple set subject areas

To create metrics against multiple subject areas defined in Set Analyzer in your universe you need to create new class structures for products and a supporting schema to query the product set information against the fact table.

The figure below shows a completed system universe that allows metrics to be built against sets of customers and sets of products. The product key is character-based, therefore, SET_SET_DETAILC is used to hold set membership information.

Performance Manager Administrator's Guide

Metric Universes

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The schema for product is very similar to that of the customer subject area. All prompt syntax is identical, and the only difference is the use of the aliases of CI_PERIOD and the sales table, and the inclusion of the product table.

There is no limit to the number of subjects that can be represented in a system universe, but Business Objects recommends that you create separate universes to simplify viewing and editing very large schemas.

Advanced Topics

Metrics on metrics

Once you have stored metric information in the performance management system tables, you can use the stored values as the basis for further metric calculations. You load the metric metadata tables into the system universe and create measure objects against these tables. Using metrics based on metrics allows you to increase performance significantly. For example, if a metric for sales and a metric for number of transactions have been defined, rather than calculate average sales per transaction against the fact table, the metric of sales can be divided by the metric for transaction, thus calculating against the aggregated metric tables only.

Example: Metric of de-seasonalized sales

InDesigner the"Edit Properties " dialog box reads as follows:

•

Name: De-seasonalized Sales

•

Type: Number

•

Description: AGGR=SUM; LIST=N;DESC=Apply a MA2x12 moving average on Monthly Sales metric. Don't calculate the last 6 periods.

•

Select:sum(probe_value_sta.prove_value*ci_peri

oc_stat.weight1)/sum(ci_period_stat.weight2)

•

Where:probe_value_sta.probe_id=8 AND ci_period_stat.id=1

AND period.period_type=4 AND period.period_overall

<=(ci_prove.end_overall-6)

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The metric takes the value of the sum of sales metric, metric id 8, and computes a MA2x12 smoothing using the weightings stored in the statistical roll up table, CI_PERIOD_STAT. The SQL is hard_coded with the IDs for the metric, the period type, and the smoothing to apply.

Note:

This can cause additional overhead should metrics be changed in the future.

The figure below shows the tables with the appropriate joins to calculate metrics against metrics using the statistical transformation tables. The self-join on the table ci_period_stat.period_date follows the same syntax as the fact table self-joins.

Tip:

When you refresh metrics first refresh the initial metric and the refresh the metric that is based on the initial metric. Business Objects recommends that you create a rule to refresh the second metric each time the first is refreshed.

Metrics functions in the rules engine

The rules engine contains a function builder that allows access to metric values. You query the metric values directly and do not use the system universe.

You define metrics as variables to be used as a condition in the "Condition Formula Editor" that you access from the "Rules" page in Performance Manager .

Metric attribute suffixes allow the metrics, when defined as variables, to be used in a condition.

• metric1.id - returns the id of the metric.

• metric1.value - returns the latest value of the metric.

These can then be used in the metric functions.

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Example:

MetricValue(metric1.id) > MetricValue(metric1.id, -1)

If the current value of metric1 is greater than the value of metric 1 for the last period.

Example:

MetricValue(metric1.id) > MetricValue(metric1.id, -12)*1.1

If the current value of metric1 has increased by 10% over the value of metric1 twelve months earlier.

Example:

ForecastCubic(MetricValues(metric1.id, 6), 7) > MetricValue(met ric1.id)

Take the last six values of metric1 and forecast the seventh point using a cubic line fit, then compare values to see if the current metric value is below this forecast.

Configuring universes for process control charts

This section explains how to create a universe for control chart analysis. You must have a working knowledge of process control charts and universe design.

The new performance management process control engine uses a Business Objects universe as metadata to access the underlying data source. The engine is capable of working with data at a transactional level, as well as at any level of aggregation, but there are a number of requirements that must be met by the data source to enable the process control engine.

The examples used below are taken from the manufacturing sample universe included with the performance management installation.

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Universe configuration

The performance management process control engine uses a number of elements from a specially configured BusinessObjects universe to access the appropriate data for each control chart.

To create a universe for the process control engine, start by inserting the appropriate fact tables that contain the transactions or aggregate values that you chart. Each fact table needs a self-join on its timestamp to allow the performance management framework to select data by date. Measures are then organized into classes which are translated into subject areas. Dimension objects for breakdown variables are also included in the appropriate classes. Conditions are created and combined to create filters for control charts. Any control chart that needs to draw data from two fact tables (p, np, or u charts) needs to include filters that are based on a common dimension that joins to both fact tables.

Measures

Measure objects in the universe are used by control charts to calculate the actual data points on the control chart. Each control chart uses either one or two measures to calculate its data points. During configuration, you select the measure object or objects that are used in the control chart calculation. Then, you organize these objects in classes that are translated into subject areas.

Each measure comes from a fact table that contains the raw data. This raw data may be at transactional level or aggregated. In the manufacturing example, the tables individual_measurement, defect, reject, and inspection are used as fact tables. For example, the fact table individual_measurement is used to construct variable control charts. In the figure shown below a number of measure objects have been created in a class called Manufacturing Variable.

Depending on the nature of the data, it may or may not be necessary to include aggregate functions in the measure objects themselves. If the values in the table are already sufficiently aggregated that no further aggregation

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is necessary, as in the individual_measurement table, then no aggregation function is included in the object.

Self-joins

Each fact table must include a self-join that is used to select values during sampling. The self-join is on the date stamp column of the fact table and follows this exact syntax. Changes in case and spaces can cause this self-join to fail.

In the Expression box of the Edit Join dialog box type the following SQL:

<date stamp column> between @Prompt('BEGIN_DT','D',,mono,free) AND @Prompt('END_DT','D',,mono,free)

Breakdown variable

Breakdown variables are used to automatically generate control charts for each value in a dimension. For each breakdown variable that is used, a dimension object needs to be created in the appropriate class in the universe.

In the manufacturing example, Reject Type is a breakdown variable in the Manufacturing Reject class. The breakdown variable can come directly from the fact table, if appropriate, or it may be an object that is based on a column in a joined table. In the case of Reject Type the object is based on reject_type.name from the joined reject_type table.

Filters

Filters are used to limit a particular control chart (or set of control charts for a breakdown variable) to a particular set of data. Control chart filters are based on combinations of conditions that are created in the universe. In the manufacturing example, the conditions include those that limit control charts to particular product type, as shown below.

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The conditions can be based on columns directly on the fact table, or any table that is joined to the fact table. When designing conditions, bear in mind that control chart filters that are configured in Performance Management can combine conditions together.

For p, np, and u charts you can draw the measures that are used in calculating control chart points from two different fact tables. In p charts, for example, the value on the control chart is calculated based on the number of rejects, which may come from one table, and the number of inspections, which may come from another table. When two tables are involved they both need to be constrained by a common filter that is based on common conditions.

In the manufacturing example the Manufacturing Reject class uses measures from two different tables. For number of rejects the Nb Rejected object are used, which is based on the reject.nb_rejected column. For the number of inspections the Nb Inspections object is used, which is based on the inspection.nb_inspected column. The common filters are based on the name field in common dimension table item.

Systematic sampling

If systematic sampling is required in a particular subject area, a dimension object is needed in the appropriate class based on the timestamp column in the fact table. For the manufacturing example the Measurement Time object

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in the Manufacturing Variable class is based on the individual_mea

suremt.measuremt_time column.

Resolving loops in the universe

The universe design to support the process control engine can often result in loops in the universe. There are two ways to deal with loops:

• table aliases

• contexts

A table alias was used in the manufacturing universe to resolve a loop. In this case the defect_type and item tables both need to be joined with the defect and reject tables creating a loop. This loop has been resolved by aliasing defect_type as reject_type for the join with the reject table.

An alternative approach, which may be necessary in some cases, is to use contexts to resolve the loop. For example, the use of two fact tables for rejects and inspections may result in a loop if a number of filter and breakdown objects are required from different dimension tables. One context can be named for the tables included in the rejects query, and one context for the inspection query.

Note:

Remember to include the self-joins in the relevant context.

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Database requirements

The database design must meet the following two requirements if it is to be used for process control charts:

• Each fact table must include a date stamp in the date/time format of that

database.

• If two tables are used in p, np, or u charts then they must have a common

dimension table that can be used for a common filter.

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Dashboard and analytic applications

BusinessObjects Dashboard and Analytics connects goals, metrics, and people in order to drive improved management, analysis, and action across the organization. Metrics offer up-to-the-minute snapshots of your key process indicators (KPIs) and tracking goals allows you to monitor day-to-day activity results.

Business Objects offers the following tools to help you mine your data for trends:

• Dashboard Builder

• Performance Manager

• Set Analysis

• Predictive Analysis

• Process Analysis

What is Dashboard Builder?

Dashboard Builder is a BusinessObjects Dashboard and Analytics application that helps you manage and track your company's performance using analytics and dashboards, as well as schedule the refresh of metrics, sets, control charts, Predictive models and analytics.

What is Performance Manager?

BusinessObjects Performance Manager helps organizations align actions with strategy. Through setting goals and tracking performance in scorecards, people can focus their efforts, collaborate with others, and follow recommended actions to improve organizational performance.

What is Predictive Analysis?

BusinessObjects Predictive Analysis quickly uncovers key business drivers from your data and forecasts future business conditions. It helps people

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make proactive decisions more easily by providing insights via easy-to-use dashboards across the organization.

What is Process Analysis?

BusinessObjects Process Analysis can be used for several purposes.

• It helps you automate the mechanics of quality control.

• It enables organizations to support quality improvement initiatives by

automatically tracking quality variables throughout the enterprise.

• It helps uncover specific business processes where there is variation and

identify opportunities for improvement, by providing powerful web-based quality management and automated control charts and alarms.

What is Set Analysis?

BusinessObjects Set Analysis helps organizations define, track and analyze segments that drive the success of business activities.

Deployment of Dashboard and Analytics tools to your organization

Before users in your organization can start working with Dashboard and Analytics applications, you need to do the following tasks.

Mandatory tasks

• Create the Performance Manager repository.

The Performance Manager repository stores the metrics, goals and calendars leveraged across your deployment.

• Define the system users.

System user accounts initialize the Dashboard and Analytics servers and enable the Dashboard and Analytics application engines.

• Connect to a universe.

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Universes provide the semantic layer that maps familiar business terms to your corporate data sources.

Note:

Users can also define metrics manually. To find out how to do this, see the Performance Manager documentation.

• Define calendars.

The calendar time periods you define are used to build the aggregated measure results for metrics over time. This allows users to perform time-series analysis on KPIs. You can create standard calendars or import custom calendars adapted to your business processes.

Optional tasks

For more powerful analysis, you can also:

• Associate users to dimensions.

Create associations to allow users to analyze sliced metrics, where the value for the metric is broken down by the values on a dimension, and lets you secure dimensions by granting access to slices to users, so that specific users can only see results for certain slices.

For example, you could select the [Sales] metric and slice it by the [Region] dimension in order to analyze sales per region. You could then secure the [Region] dimension so that users working in a specific regional sales office could only see sales results for their region.

• Apply statistical calculations such as moving average, difference, or rollup

to selected calendars.

You use statistical calculations for smoothing and aggregating time-series. For more information, see the chapter in the documentation about Performance Manager calendars.

Related Topics

• Overview of the Dashboard and Analytics deployment on page 65

• Moving averages in calendars on page 105

• Rollups in calendars on page 113

• The Performance Manager repository on page 65

• Dashboard and Analytics system users on page 77

• Metric universes on page 79

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• Analytics calendars on page 97

• Sliced metric dimensions on page 88

Performance Manager servers

The following table provides a description of each Performance Manager server:

DescriptionServiceServer name

Performance Manager servers

AADashboard

AAIProfiler

AARepomgt

Dashboard engine

Analytics serverAAAnalytics

Metrics engineAAMetrics

Individual Profiler engine

Repository manager

Renders dashboards created in Dashboard Builder.

Renders the analytics by querying the metrics metadata and then generating the desired visualization in the format of the selected analytic.

Works like an ETL tool to extract each metric value, aggregate it, and then load it into the metadata layer on the Performance Manager repository.

Used by the Individual Profiler analytic.

Manages the Performance Manager repository – including user security and privileges, updates to the system parameters, and writing new metrics and rules back to the repository.

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Performance Manager servers

Rules engineAARules

DescriptionServiceServer name

Evaluates conditions placed against metrics, goals, sets and then outputs sending events to other components

AAQueryManager

PAServer

Related Topics

• Individual Profiler portrait properties on page 127

Set Analysis query manager

SPC engineAASPC

Predictive Analysis mining engine

Performs Set Analysis queries and builds and processes sets.

Used by Process Analysis.

Note:

The SPC alerts are actioned upon and handled by AARules

Used by Predictive Analysis. For more information, see the Predictive Analysis documentation.

Performance Manager server options

In Dashboard and Analytics Setup > Parameters > Options, set the following options:

• Mail Parameters

These parameters contain details of the Dashboard and Analytics SMTP server, port number, and email address used to send automated emails for alerts, rules, and generated lists.

• Web Parameters

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These parameters contain details of the web server including the port number, host name, and the login URL.

• General Parameters

These parameters contain details of date and number formats applied across Dashboard and Analytics applications, SQL query optimization parameters, Individual Profiler query limits, and the frequency for information on external events stored in the Central Management Server to be written to the Performance Manager repository.

• Scheduler Parameters

These parameters contain details of the directory used to cache scheduler processes and the user account associated with those processes.

• Database Parameters

These parameters contain details of the minimum number of database connections you wished to be kept open for a specific Dashboard and Analytics engine.

Setting mail parameters for Dashboard and Analytics applications

You need to specify mail parameters so that users can use the email features within Dashboard and Analytics applications. For example, users can build rules, alerts, and lists that generate emails and have the ability to email some of the analytics.

1. Go to Dashboard and Analytics Setup > Parameters > Options.

2. In the "Mail Parameters" section, configure the following parameters:

• "Outgoing SMTP server"

Type the name of the Dashboard and Analytics server from which automated emails, such as email alerts and email lists, are sent.

• "SMTP Port Number"

Enter the port number of the SMTP (Simple Mail Transfer Protocol) server.

• "From Address"

Type the email address of the SMTP server that appears in the "From" field in email messages.

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Performance Manager servers

• "Reply to Address"

Type the address to which automatic replies are sent. This is usually the same as the "From Address".

3. Click Apply.

Any modifications you made are applied the next time you restart the Dashboard and Analytics server.

Specifying web parameters for Dashboard and Analytics applications

By default, the web server used for Dashboard and Analytics applications is the same server on which Dashboard and Analytics is installed. The "Web Parameters" options allow you to specify a remote web server. If you performed a custom installation and defined a custom URL for end users to use to access the InfoView login page, then you need to type the custom URL you defined here.

Note:

For information on performing a custom installation, see the BusinessObjects Enterprise installation guide available at: http://support.businessob

jects.com/documentation.

1. Go to Dashboard and Analytics Setup > Parameters > Options.

2. In the "Web Parameters" section, configure the following parameters:

• "Web server host name"

Type the name of the web server that host Dashboard and Analytics applications.

• "Web server port number"

Enter the port number of the host web server.

• "Performance Manager URL"

Type the URL that end users use in their web browser to launch the InfoView home page.

3. If you want to process XLS transformations on the client machines used

by end users across your deployment, activate Push XLS transformations to the client.

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Performance Manager servers

You can opt to process the XSL transformations, for example for SVG format analytics, to the client instead of processing them on the server. This helps lighten the load on the server, by passing the cost of the transformation onto the client.

Note:

We recommend that you compare performance of processing the XLS transformations on the client against processing the XLS transformations on the server, in order to make the best decision for your deployment. The optimum choice can differ depending on the client machines used on your deployment and the number of concurrent users taxing the server.

4. Click Apply.

Any modifications you made are applied the next time you restart the Performance Manager server.

General parameters for Dashboard and Analytics applications

The "General Parameters" options allow you to:

• specify settings for number and date formats displayed on dashboards

• optimize SQL query processing

• limit the size of Individual Profiler queries

• specify how often the data for external events stored on the Central

Management Console (CMC) is sent to the Performance Manager repository.

Note:

External events defined on the CMC are used in Performance Manager rules or alerts to trigger specific actions. For information about including external events on the CMC, see the BusinessObjects Enterprise administration documentation.

Related Topics

• Specifying general parameters in Dashboard and Analytics Setup on

page 59

Specifying general parameters in Dashboard and Analytics Setup

1. Go to Dashboard and Analytics Setup > Parameters > Options.

2. In the "General Parameters" section, configure the following parameters:

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"Number Format"

•

Select a number format for analytics and dashboards.

• "Date Format"

Select the date format for analytics and dashboards.

• "Maximum Number of Columns for Optimized SQL"

Select a number to apply to SQL queries for analytics and documents. The option allows Dashboard and Analytics to group SQL from columns in the same table, for the number of columns you specify, and so optimizes the calculation process.

• "Individual Profiler Maximum Query Size"

Select the limit for the maximum number of rows returned for an Individual Profiler query.

• "BusinessObjects Enterprise Events Polling Time"

Select the amount of time between two polling events, measured in seconds. The option specifies how often Dashboard and Analytics checks for an event on the Events server in the CMC, and therefore ensures that any new external events on the CMC are written to the Performance Manager repository for use in rules and alerts.

3. Click Apply.

Any modifications you made are applied the next time you restart the Dashboard and Analytics server.

Related Topics

• Individual Profiler portrait properties on page 127

Specifying scheduler parameters for Dashboard and Analytics applications

If their security profile allows, end users can schedule Dashboard and Analytics tasks, such as refreshing metrics. As an administrator, you can specify the location of the directory used to cache scheduler processes and specify the user account associated with the processes.

1. Go to Dashboard and Analytics Setup > Parameters > Options.

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2. In the "Scheduler Parameters" section, type the appropriate information

in the following text boxes:

• "Scheduler working directory"

The directory path that appears in the text box comes from information provided at installation.

• "Scheduled programs will run under this user account"

The user name and password used should be for machine on which you installed the Dashboard and Analytics applications.

Note:

If you change the parameters, any existing schedules become incorrect. To update the definition of existing schedules to the new schedule parameters, run the "Scheduled Programs""Check & Cleanup" tool at Dashboard and Analytics Setup > Tools > Check

Integrity and Cleanup.

3. Click Apply.

Any modifications you made are applied the next time you restart the Dashboard and Analytics server.

Specifying database parameters for Dashboard and Analytics applications

The "Database Parameters" allow you to specify the minimum number of database connections kept open for a specific Dashboard and Analytics engine. This optimizes performance.

1. Go to Dashboard and Analytics Setup > Parameters > Options.

2. In the "Database Parameters" section, click the drop-down arrow in the

text box on the right.

The list of Dashboard and Analytics engines appears.

3. Select the engine for which you want to specify the minimum number of

open database connections:

• Analytics

The Analytics server renders the analytics by querying the metrics metadata and then generating the desired visualization in the format of the selected analytic.

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• Repository Management

The repository manager manages the Performance Manager repository including user security and privileges, updates to the system parameters, and writing new metrics and rules back to the repository.

• Process Analysis Engine

Process Analysys uses this engine.

• Metrics Engine

The metrics engine works like an ETL tool to extract each metric value, aggregate it, and then load it into the metadata layer on the Performance Manager repository.

• Mining Engine

Predictive Analysis uses this engine.

• Rules Engine

The rules engine evaluates conditions placed against metrics, goals, sets and then outputs sending events to other components.

• Query Manager

The query manager performs Set Analysis queries and builds and processes sets.

• Profiler

The Individual Profiler uses this engine.

4. Enter the number of connections you want open concurrently for the

selected engine into the "Minimum Number of Database Connections Kept Open" text box.

5. Click Apply.

Any modifications you made are applied the next time you restart the Dashboard and Analytics server.

Server caching parameters

The cache refresh period settings determine how often Dashboard and Analytics refreshes the server caches with the latest values on the Performance Manager repository and the Central Management Server (CMS).

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In multi-node deployments, it is important to set the cache refresh and clean-up periods to ensure that the Dashboard and Analytics servers across your deployment reflect the same definitions of metrics and analytics to end users.

Cache refresh and clean-up settings

You can specify the following cache refresh periods and clean-up periods:

• "Metadata Cache Refresh Period" – used to cache metrics, goals, and

sets. For example, you look at a speedometer the values displayed come from this cache.

• "App Designer Cache Refresh Period" – used to cache the XML definition

of dashboards

• "Server Session Cache Clean-up Period" – used to cache session

information

• "Corporate Dashboard Cache Refresh Period" – used to cache corporate

dashboards

Modifying a cache refresh or clean-up period

1. Go to Dashboard and Analytics Setup > Parameters > Caching.

2. In the text box next to the option you want to modify, type the number of

minutes you want to set as the frequency for the cache refresh or clean-up.

3. Click Apply.

Performance Manager servers

The settings are applied immediately.

Dashboard and Analytics launch errors

If you launch Dashboard and Analytics and an error message appears that says that you cannot connect to Dashboard and Analytics, it is for one of the following reasons:

• Some of the Dashboard and Analytics servers are stopped or disabled.

• The Initialization User that creates the Dashboard and Analytics server

proxies was defined inconsistently in the Central Management Server, InfoView, and the InitConfig.properties file.

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Verifying the Dashboard and Analytics servers

1. Log into the Central Management Console (CMC), and then click Servers.

2. Verify that all the Dashboard and Analytics servers are started.

3. If a server is not running, select the check box next to the server name,

and then click Start.

4. Make sure that all servers are enabled.

If a server is not enabled, select the check box next to the server name, and then click Enable.

Related Topics

• Performance Manager servers on page 55

Verifying the Initialization User

1. On the Dashboard and Analytics server, open the InitConfig.properties

file and verify that the Initialization user name and password match those in the Central Management Server (CMS).

The InitConfig.properties file is located in the following location:

[Install Directory]\Program Files\Business Objects\Performance Management 12.0

The strings to search for are:

• initialization.User=

• initialization.Password=

2. Log into InfoView, and then click the "Preferences" button on the InfoView

toolbar.

3. In the "Dashboard and Analytics" tab, check the name of the initialization

logon user in the "Change initialization logon user" section is the same as that specified in the InitConfig.properties file.

4. Log into the Log into the Central Management Console (CMC), and then

click Users.

5. Check that the user defined in the InitConfig.properties is listed among

the users.

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6. From the CMC home page, click Settings > Rights and check that the

initialization user has the appropriate rights.

Note:

For security reasons, it is recommended that you do not provide a real user ID for the initialization user. The default user ID is PMUser.

7. In the Central Configuration Manager, restart all of the servers.

Note:

If you are using Dashboard and Analytics from a client machine, restart the client machine.

The Performance Manager repository

The Performance Manager repository is organized as follows:

• Performance Manager tables – store the calendars, metrics, rules, goals

and target values used by Performance Manager.

• Set Analysis tables – store the sets for the segmentation engine used by

Set Analysis.

Note:

If this is the first time you have installed Dashboard and Analytics, you need to create the Performance Manager repository before users can start to work with Dashboard and Analytics applications.

Related Topics

• Creating the Performance Manager repository on page 67

Overview of the Dashboard and Analytics deployment

A Dashboard and Analytics deployment includes two repositories:

• The Central Management Server (CMS) database – stores user security

information, documents, dashboards, analytics, performance models, schedules and the semantic layer that maps to your corporate data sources (for example metric universes and business views).

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• The Performance Manager repository – stores the metrics, calendars,

goals, and sets specific to Dashboard and Analytics.

Note:

In previous Dashboard and Analytics versions, the Performance Manager repository was called the Performance Management repository and the Application Foundation repository (or AF Repo). In Application Foundation

6.x versions and earlier, the equivalent to the CMS was the BusinessObjects repository.

The system tables stored in the repository

The Performance Manager repository stores information used in various groups of tables used by different Dashboard and Analytics applications:

• Tables with the ci_ prefix store the metrics, rules, calendars used by

Performance Manager, for example, the ci_probe_value.

Note:

Each time users refresh a metric in Performance Manager, the data is retrieved from the universe or manual metrics data source, calculates the values according to the calendar period you defined, and writes those values to the Performance Manager repository.

• Tables with the ipm_ prefix store the metadata related to publishing, next

actions, and strategy builder used by Performance Manager.

For example: ipm_analytic

• Tables with the set_ prefix store sets used in Set Analysis.

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For example: set_sig_field

Creating the Performance Manager repository

When you install Dashboard and Analytics, you need to:

• create a connection to the target database you selected for the

Performance Manager repository.

• deploy the system tables to the Performance Manager repository so that

users can start to use Dashboard and Analytics applications.

Note:

The Total Electronics demo database is designed to accompany the sample dashboards shipped with the Dashboard and Analytics applications. We recommend that you do not use this demo database as the basis of your corporate Performance Manager repository.

• verify the options, such as encoding, applied to the new Performance

Manager repository.

Note:

To create the Performance Manager repository, and to make any modifications in "Dashboard and Analytics Setup", you need to be logged into InfoView as an administrator.

Creating a connection for the Performance Manager repository

If this is the first time you have installed the Dashboard and Analytics applications, you need to create a connection to the database on which you want to store the Performance Manager repository. You do this using Designer.

1. Launch Designer.

2. In the "Connections" list, select Tools > Connections, then click Add.

3. Follow the instructions in the "New Connection Wizard".

For full information, consult the Designer documentation about working with connections.

4. Verify the connection to the Performance Manager repository.

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Related Topics

• Performance Manager repository migration on page 71

• Verifying the connection to the Performance Manager repository on

page 68

Verifying the connection to the Performance Manager repository

Note:

If this is the first time you have installed Dashboard and Analytics, you need to create a connection to the Performance Manager repository.

1. Go to Dashboard and Analytics Setup > System Setup > Repository.

2. In the "Repository Information display" section, click Check.

If there is a problem with the connection, an error message provides details.

Related Topics

• Creating a connection for the Performance Manager repository on page 67

Deploying the system tables using Dashboard and Analytics setup

You need a connection to the target database before you can deploy the system tables.

To deploy the system tables to the target database you have chosen as the Performance Manager repository:

1. Go to Dashboard and Analytics Setup > System Setup > Repository

> Repository Information.

2. Click the drop-down arrow next to connection name.

3. Select the target database from the drop-down list.

The "System Tables Management" display section advises you whether the system tables have been installed or not. If an earlier version of the product has been installed, the module detects it and suggests an upgrade. To upgrade the repository, click Upgrade.

4. The repository creation script runs.

5. Do one of the following:

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To deploy the tables now to Dashboard and Analytics, click OK.•

• To deploy the system tables via an external application, click Select

All, and then copy and paste the script into the external application.

6. Log off InfoView, and then restart all servers using the Central

Configuration Manager (CCM).

Related Topics

• Creating a connection for the Performance Manager repository on page 67

Verifying the options applied to the Performance Manager repository

The repository options let you specify settings optimized for the type of database you are using for the Performance Manager repository. You can view the options applied to the repository and change the options if necessary.

1. Go to Dashboard and Analytics Setup > System Setup > Repository

and click View Options.

The selected encoding appears in the "Encoding" box.

Encoding can be set while defining the connection to the repository or during the repository creation.

Note:

By default, the encoding for Dashboard and Analytics is Unicode (UTF-8). For encoding other than Unicode (UTF-8), the database and the processes go through a convertor, so performance is slower.

2. To change the encoding, click the arrow next to the "Encoding" box, and

select the appropriate encoding from the list.

Note:

For certain databases, the following advanced options are activated and allow you to customize the repository environment:

• Tablespace

• Index Post Script

• Numeric Keys Precision

• Use Long Integer Fields

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Related Topics

• Creating a connection for the Performance Manager repository on page 67

• Creating the Performance Manager repository on page 67

Central Management Server authentication

Access to the features in Dashboard and Analytics Setup is authenticated against the Central Management Server (CMS). The CMS controls security, such as which users or groups have access to which dashboards.

There are several types of authentication for BusinessObjects Enterprise and Dashboard and Analytics:

• "Enterprise" – the system default authentication. This is recommended if

you prefer to create distinct accounts and groups for use with BusinessObjects Enterprise, or if you have not already set up a hierarchy of users and groups in a Windows NT user database, an LDAP directory server, or a Windows AD server.

• "LDAP" – Lightweight Directory Access Protocol. This is recommended

if you want to integrate Dashboard and Analytics authentication with a single list of authorized users and passwords for your enterprise web, email, and file-sharing servers.

• "Windows NT" or "Windows AD" – You can also use Windows NT

authentication (for Microsoft Windows NT) or Windows AD authentication (for Windows 2000).

You can verify the CMS authentication and change the authentication, if you wish.

You can also point your Dashboard and Analytics server to a different CMS. This is particularly useful if your deployment includes multiple CMS databases used for different environments. For example, you may have one CMS for your development environment and another CMS for your production environment.

Note:

• For information on how to setup CMS authentication, refer to the

BusinessObjects Enterprise administrator's guide available at:

http://support.businessobjects.com/documentation.

• To modify parameters in Dashboard and Analytics Setup you need to

be logged into InfoView as an administrator.

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Verifying or changing the Central Management Server authentication

1. Go to Dashboard and Analytics Setup > System Setup > Repository.

The name of the web server where the Central Management Server (CMS) is installed appears by default in the "CMS Name" box.

2. If you want to redirect to another CMS, type the name of the CMS using

the following syntax:

<server_name>.<server_domain>

For example: myserver.marketing.mycompany.com

The authentication appears in the "Authentication" box.

3. If you want to select a different authentication, click the arrow next to the

"Authentication" box and select the type of authentication you want from the list.

Performance Manager repository migration

You can migrate the Performance Manager repository from a different environment or from a previous version. The following table tells you which white paper or guide provides information on each of the possible migration paths:

DocumentationMigration path

a test environment to a production environment

Application Foundation 6.5.x to Performance Management XI R2 and higher

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DocumentationMigration path

Performance Management XI to Performance Management XI R2 and higher

Tip:

All documentation is in Adobe PDF format and available at: http://support.busi

nessobjects.com/documentation.

BusinessObjects Enterprise installation guides

Performance Manager repository integrity and cleanup

In Dashboard and Analytics Setup > Tools the "Check Integrity and Cleanup" section allow you to perform an integrity check on the following information stored in the Performance Manager repository:

• Universes

The metric universes stored on the Performance Manager repository.

• Rules

The rules set up using Performance Manager.

• Metrics

The metrics defined using Performance Manager.

• Alerts

Email alerts (triggered by events) created using Performance Manager.

• Users

User accounts already defined in the system.

Note:

You cannot remove users while they are logged into "Dashboard and Analytics".

• Predictive Analysis

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The populations, variables, binnings, models, and advanced metrics defined using Predictive Analysis.

• Scheduled Programs

"Scheduled Programs" allows you to update the scheduling parameters for a pre-existing scheduled program to match those currently specified in Dashboard and Analytics Setup > Parameters > Options > Scheduler Parameters.

These tools help you to remove faulty or redundant data from the Performance Manager repository.

Note:

Erasing any of the entries physically removes them from the Performance Manager repository database.

Checking system universe integrity in the Performance Manager setup

Checking the integrity of the metric universes enables you to ensure that the universes used to define Dashboard and Analytics metrics work correctly.

1. Go to Dashboard and Analytics Setup > Tools.

2. In the "Check Integrity" section, click Universe.

The "Check Integrity" window appears.

Any universes that contain errors are flagged here.

3. To find out more information about an error, click the universe.

The errors are detailed in the "Check Details" section.

For information about resolving errors in universes, refer to the Designer documentation available at http://support.businessobjects.com.

Checking the integrity of Performance Manager rules

Checking rules allows you to ensure that any rules based on events, created by Dashboard and Analytics users, function correctly.

1. Go to Dashboard and Analytics Setup > Tools.

2. In the "Check & Cleanup" section, click Rules.

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Any rules that include errors are listed. You can delete rules here or modify rules in Performance Manager.

3. To delete a rule, select the rule you want to delete and click Erase.

Note:

To modify a rule, exit Dashboard and Analytics Setup, open Performance Manager and in the "Rules" tab, select the rule and click Edit. See the Performance Manager documentation for information on editing rules.

Checking the integrity of Performance Manager metrics

Checking metrics allows you ensure that the metrics created and analyzed by Dashboard and Analytics users function correctly.

1. Go to Dashboard and Analytics Setup > Tools.

2. In the "Check & Cleanup" section, click Metrics.

The "Check & Cleanup Metrics" window appears.

Any metrics that contain errors are flagged here.

3. To find out more information about an error, click the metric.

The errors are detailed in the "Check Details" section.

4. To delete a metric, select the metric you want to delete and click Erase.

Checking the integrity of Performance Manager alerts

Checking alerts allows you to ensure any alerts created by Performance Manager users function correctly.

1. Go to Dashboard and Analytics Setup > Tools.

2. In the "Check & Cleanup" section, click Alerts.

The "Check & Cleanup Alerts" window appears. Any alerts that contain errors are flagged here.

3. To find out more information about an error click the alert.

The errors are detailed in the "Check Details" section.

4. To delete an alert, select the alert you want to delete and click Erase.

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Checking the integrity of Performance Manager users

Checking users allows you to remove user accounts that fail the integrity test from the Central Management Server (CMS).

1. Go to Dashboard and Analytics Setup > Tools.

2. In the "Check & Cleanup" section, click Users.

The "Check & Cleanup Users" window appears. Any user profiles that contain errors are flagged here.

3. To find out more information about an error click the user name.

The errors are detailed in the "Check Details" section.

4. To delete a user, select the user you want to delete and click Erase.

Note:

You cannot delete users who are currently logged into Dashboard and Analytics.

Checking the integrity of Predictive Analysis objects

You can check the integrity of the populations, variables, binnings, models, and advanced metrics defined using Predictive Analysis.

1. Go to Dashboard and Analytics Setup > Tools.

2. In the "Check & Cleanup" section, click Predictive Analysis.

The "Check & Cleanup Predictive Analysis" window appears.

3. Click the drop down arrow next to the list box at the top of the window,

then select the subject area for which you want to make the integrity check.

Any populations, variables, binnings, models or advanced metrics that include errors are listed and more information about each error is provided in the "Check Details" section.

4. To delete a service, select the Predictive Analysis service you want to

delete and click Erase.

Note:

You cannot delete users who are currently logged into InfoView.

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Checking the integrity of parameters for a scheduled program in Dashboard and Analytics Setup

The scheduling parameters integrity check verifies:

• the user name and password specified as the user account for scheduled

programs.

By default, it is the user account for the operating system on which Dashboard and Analytics is installed (for example, the NT user account).

• the working directory in which the scheduled programs are run.

Note:

The schedule parameters can be modified in Dashboard and Analytics Setup > Parameters > Options > Scheduler Parameters.

It is recommended you check the parameter integrity whenever the Scheduler Parameters are modified, so that any existing scheduled programs are updated to match the new parameters.

Some typical situations that cause errors to occur include:

• the scheduled account user password changes for security purposes.

• the scheduling program working directory changes from one drive to

another to suit disk capacity needs.

• the system is migrated to a new environment, and so the scheduling

parameters need to be updated.

1. Go to Dashboard and Analytics Setup > Tools > Check & Cleanup.

2. Click Scheduled Programs.

The "Check & Cleanup Scheduled Programs" window appears, displaying the current scheduling user name and working directory, as well as a list of all the currently existing scheduled programs that do not having matching parameters.

For each inconsistency, the tool lists the task id, description, username, whether the password matches, working directory, start date, end date, and period type.

3. To update the parameters of a schedule to the current scheduling

parameters, select the schedule you want to update and then click Fix. To update all the schedules with erroneous parameters, you can click

Select All, then Fix.

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Dashboard and Analytics system users

Before users in your organization can use Dashboard and Analytics applications, you need to specify system users in "Dashboard and Analytics Setup". These users initialize the Dashboard and Analytics servers and enable the engines for Performance Manager and Set Analysis.

Note:

To modify the users defined in Dashboard and Analytics Setup, you need to be logged into InfoView as an administrator.

Defining a Dashboard and Analytics system user

Specifying a Dashboard and Analytics system user enables the Performance Manager engine, which end users need for goals.

Note:

The system user must have Administrator rights specified in the Central Management Console (CMC). For information on how to set security rights for Dashboard and Analytics, see the BusinessObjects Enterprise administrator documentation.

1. Go to Dashboard and Analytics Setup > System Setup > System

User.

2. In the "System User" section, type Administrator in the "User Name" text

box.

3. In the "Password" box, type the password.

By default, there is no password for Administrator. It is strongly recommended that you define a password for the Administrator user. See the BusinessObjects Enterprise administrator documentation for information on passwords.

4. To verify that the CMC recognizes the user as a user with administrator

rights, click Check.

Note:

If an enterprise authentication error appears, the user name you entered does not have Administrator rights allocated to it in the CMC. You need to either launch the CMC and modify the security profile of the user, or

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enter a different user name that already has administrator rights in the CMC.

5. To save the new user, click Apply.

Defining a Dashboard and Analytics Set Analysis guest user

Typically, only a small number of users in a deployment create sets. Most users use existing sets to build metrics when they use Performance Manager.

Specifying a Set Analysis guest user enables all valid Dashboard and Analytics users to use sets. End users who do not have a profile to create sets automatically borrow the Set Analysis guest user profile when they open Dashboard and Analytics. The guest user allows users to visualize sets for metric creation and analysis.

Note:

Before you can define the Set Analysis guest user, you need to set a user in the Central Management Server (CMS) that has all of the Set Analysis features enabled. You create the user in the CMS in the Central Management Console. For information on how to do this, refer to the BusinessObjects Enterprise administrator documentation.

You need to then create the same user in Set Architect, the Windows setup application designed for Set Analysis. For information on how to set up the Set Analysis guest user in Architect, refer to the Set Architect online help.

1. Verify that the Set Analysis guest user exists on the CMS and has all the

Set Analysis features enabled.

2. Verify that the same Set Analysis guest user is defined in Architect.

3. Go to Dashboard and Analytics Setup > System Setup > System

User.

4. In the "Set Analyzer Guest User" section, type the guest user name in

the "User Name" text box.

Note:

The Set Analysis guest user you type here must also be set up as a guest user in Architect.

5. To verify that the user is a known user, click Check.

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Note:

If an enterprise authentication error appears, the user name you entered is not registered as a guest user in Set Architect. If this is the case, you need to launch Architect and create a guest user.

6. To save the new user, click Apply.

Defining a Dashboard and Analytics Initialization user

Specifying the Initialization User allows Dashboard and Analytics to initialize the Dashboard and Analytics servers and create the proxies in the server cache.

Note:

For security reasons, it is recommended that you do not allocate Administrator rights to the Initialization user and that you do not re-use a real user profile. The default user ID is PMUser, defined as a member of the Everyone user group.

1. Go to Dashboard and Analytics Setup > System Setup > System

User.

2. In the "Initialization User" section, type in a valid user in the User Name

text box.

3. In the "Password" box, type the password.

4. To verify that the user is recognized by the Central Management Server

(CMS) as a user with Dashboard and Analytics rights, click Check.

Note:

If an enterprise authentication error appears, this means that the user name you entered does not exist in the CMS. If this is the case, you need to launch the Central Management Console, create the user, and assign that user Everyone rights. You can then return to step 1, above.

5. To save the new user, click Apply.

Metric universes

The data for metrics can be supplied from metric universes built using Designer or from data entered manually using Performance Manager.

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Metric universes

This section gives you information on:

• Metric universes

• Making universes available to users

Note:

For information about entering metrics manually refer to the Performance Manager documentation.

Related Topics

• About metric universes on page 80

• Making metric universes available to Dashboard and Analytics users on

page 81

About metric universes

Metric universes contain the metrics and goals used by Dashboard and Analytics users across a deployment. When you design universes for use with Dashboard and Analytics, you need to follow specific design guidelines to generate metrics.

For example, metric universes include a time parameter that allows users to associate values of a specific calendar to the metric they want to analyze. To create a time parameter, you need to define a query condition on a date object.

Note:

The Performance Manager repository allows 34 characters as the maximum length of the universe name.

Each time a metric is refreshed, the metric values for the selected calendar are stored in the Performance Manager repository. This lets users analyze metrics over time, and so perform time-series analysis on KPIs.

Note:

On metric universes, aggregates do not need to be defined for measures at the universe level. This lets users apply different aggregate calculations when they build metrics on the measures in Dashboard Builder. However, if you select a metric universe to build an ad hoc query, using Web Intelligence for example, measures are aggregated at the report level and thus slow down the query run time.

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Metric universes

Related Topics

• Overview of the Dashboard and Analytics deployment on page 65

Building metric universes

You build metric universes using Designer. For step-by-step information on how to build universes and metrics universes see the Designer documentation, available at: http://support.businessobjects.com/documenta

tion.

Making metric universes available to Dashboard and Analytics users

Once you have a universe defined in Designer, you need to make the universe available to Dashboard and Analytics users by following these steps:

• export the universe to the Central Management Server.

For step-by-step information on how to export universes see the Designer documentation.

• add the universe to the Performance Manager repository.

Note:

You build metric universes using Designer. For step-by-step information on how to do this, see the Designer documentation, available at: http://sup

port.businessobjects.com/documentation.

Related Topics

• Adding a universe in Dashboard and Analytics Setup on page 82

Defining connections for universes

A universe is the semantic layer that maps familiar business terms to table structures in a database. Dashboard and Analytics users to select data from universes for metrics and analytics.

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Metric universes

In order for data to be retrieved for metrics and analytics, a connection to the specific database upon which the universe is mapped is defined in Designer. For information specifying connections for universes, see the Designer documentation, available at: http://support.businessobjects.com/doc

umentation.

Adding a universe in Dashboard and Analytics Setup

Dashboard and Analytics users select source data from universes for metrics and analytics. To make a universe available to end users, you need to add the universe to the Performance Manager repository.

When you add a universe, certain elements that Dashboard and Analytics applications need to build the SQL for the metrics are taken from the system database and stored on the Performance Manager repository in the following

ci_ system tables:

• ci_source – contains the reference to the universe name

• ci_subject – contains the class names

• ci_variable – contains the names of the objects

• ci_condition – contains the conditions (or query filters)

1. Go to Dashboard and Analytics Setup > System Setup > Universes.

2. Click Add Universe.

3. In the "Add a Universe" panel, select a universe.

If the universe does not appear, click the refresh icon next to the "Measure Universe" list box to refresh the list of available universes. The name of the universe and the name of the folder where the universe is located appear in the "Name" and "Folder" boxes.

All the connection information is retrieved using the connection server.

4. Click OK.

A message appears confirming that the universe has been added successfully.

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Metric universes

Updating a universe in Dashboard and Analytics Setup

1. Go to Dashboard and Analytics Setup > System Setup > Universes.

2. In "Universe Definition", select the universe you want to update.

3. If there are analytics based on the metrics using the selected universe,

activate Update Metrics and Control Charts Definitions. This option, when activated, forces the update of the SQL definitions of each metric according to the latest universe definition. When the option is deactivated, all metric properties are updated except for the SQL definitions.

When this option is activated and you update a universe, all of the analytics and metrics based on the selected universe are updated to reflect the new definition of the universe.

4. Click Update

The information on the universe in the Performance Manager repository is updated.

Removing a universe from the Performance Manager repository

You can remove universes from the Performance Manager repository.

Note:

If you have metrics or goals based on a universe you want to delete, a message appears proposing to remove these metrics and goals along with the universe itself.

1. Go to Dashboard and Analytics Setup > System Setup > Universes

> Universe Definition.

2. Select the universe you want to remove.

3. Click Remove Universe.

4. If metrics and goals refer to the universe, a message appears that

suggests that you remove these metrics and goals along with the universe itself.

5. If no warning message appears, click OK.

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Metric universes

The universe is removed from the Performance Manager repository.

Object metadata in universes

You can view the objects, sets, and filters on metrics universes once you have pushed the universe to the Performance Manager repository. You can check that any changes you have made to a universe are reflected in the pushed universe on the Performance Manager repository.

You can:

• view the measures and dimensions to verify the SQL for the measures

on universes.

• view the conditions and subsets to see the descriptions of conditions (or

query filters) and subsets.

Note:

If you notice anything incorrect, you can open the universe using Designer, and then make the necessary corrections. Information this is provided in the Designer documentation at http://support.businessobjects.com/documenta

tion.

Viewing universe measures and dimensions

1. Go to Dashboard and Analytics Setup > System Setup > Universes

> Universe Definition.

2. Select the universe you want to verify.

3. The next step depends on what type of objects you want to view on the

universe:

• If you want to view metadata for measures and dimensions, select

Measures & Dimensions.

• If you want to view conditions (query filters) or subsets, select

Conditions & Subsets.

The objects on the selected universe appear in the Available objects list.

4. To view details of an object select the object in the "Available objects"

list.

The following information appears:

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"Temporal"

"Appear in list"

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Metric universes

DescriptionField

If the value here is Yes, the selected dimension or measure is set-based. A temporal measure is a measure that used against time-based sets, as well as static sets and enterprise calculations.

If the value is Yes, the selected dimension or measure is set-based and can be used in a list.

Note:

• In order for an object to be made available for a list,

the LIST=N tag needs to be typed into the "Description" field of the object properties dialog box, using Designer. Objects that have a lot of data associated with them may not be suitable for use in lists, since lists can be very long and take time to generate.

• For more information about designing universes,

see the Designer documentation at: http://sup

port.businessobjects.com/documentation.

Provides the number format for the metric as defined

"Format"

"Aggregation"

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for the measure at the universe level, using Designer.

Provides the aggregation function applied to the object at the universe level, using Designer. For example: SUM and MIN.

The aggregation functions applied to the selected object depend on the source database. To see the aggregation calculations applied, view the ci_aggre table on the Performance Manager repository. The table lists all the aggregation functions you can use and gives their help function.

For detailed information on each aggregation function, see the Terms and concepts section.

Performance Manager Setup and Administration Online Help

Metric universes

DescriptionField

Contains the description from th euniverse level.

When designing universes for Dashboard and Analytics, the object "Description" field can be used to inform the Dashboard and Analytics server that an

"Description"

object has an aggregate function applied at the universe level. This prevents users from being able to select an additional aggregate function when they build metrics on that object using Dashboard Builder. For information about designing universes for Dashboard and Analytics, see the Designer documentation.

"SQL"

External metric refresh

A metric can have one of two refresh types, "Independent" or "External" refresh, that is applied in the metric's properties in Performance Manager.

An Internal refresh can be refreshed using the metric engine, however it requires a link to a database supported by the metric engine. If you have a database or database connection that is not supported by the metric engine, you need to use the external refresh to delegate the refresh of the metric to an external process.

To be able to create a metric with an external refresh, you need to connect to a metric universe that has no executable_sql statement and have modifications made to the ci_probe_values table after the metric is created. The entire process for configuring an external metric refresh is available in the BusinessObjects deployment documentation.

The SQL select statement used to retrieve the data for the measure from the database.

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Configuring an external metric refresh

This procedure contains steps that require Administrator permission. For these steps, if you do not have the proper permissions, contact your Business Objects administrator.

1. In Designer in an existing or new universe, create a new measure that

contains no executable_sql statement, and export it to the Central Management Server.

2. In Dashboard and Analytics Setup, push the universe to the

Performance Manager repository.

3. Create a metric based on the new measure and in the "Refresh Type"

category, activate External refresh.

4. In the Performance Manager repository database execute the following

SQL statement in the probe_id:

Select * from ci_probe where probe_id=<your id> Select * from ci_probe_value where probe_id=<your id>

Note:

The ci_probe_value is initially empty.

Metric universes

5. Populate the ci_probe_value table with relevant data.

The following table is an example of a ci_probe_value table containing populated data:

probe_id

6. Populate the following columns in the ci_probe table (all other columns

are updated when the metric is created):

end_date- 6/1/2000

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peri od_type

peri od_date

dim_keyprobe_dim_id

probe_val ue

1162796005/1/200010171

1515285006/1/200010171

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Sliced metric dimensions

where the date is 6/1/2000 until you have populated the data in ci_probe_value table. In the following example the column tells the user at what time the metric was refreshed.

refresh_date- 11/15/2006 4:47:01 PM

7. Save your changes.

8. Restart all of the AA processes.

9. In Dashboard and Analytics, create an analytic and choose the newly

created metric. The external metric refresh data now appears.

Related Topics

• Adding a universe in Dashboard and Analytics Setup on page 82

• Updating a universe in Dashboard and Analytics Setup on page 83

Sliced metric dimensions

Dimensions enable you to create sliced, or dimensioned metrics. A metric is sliced when it is divided into separate slices of data to enable a more detailed analysis.

For example, a Sales Revenue metric can be sliced by the Country dimension, so that the revenue can be analyzed by individual countries or cities, depending on the number of slices available.

What are dimensions and sliced metrics?

You obtain slice of data by applying a dimension to a metric. When you refresh a sliced metric, a value is calculated for each distinct value of the associated dimension.

For example, when you refresh the Sales Revenue sliced by the Country dimension, sales revenue is calculated and returned for each country in the metric universe.

Metrics can be sliced on different dimensions for display or security reasons. For example, a large organization can slice a metric and restrict access to specific slices, so that employees can only view data related to a specific activity. The organization can apply an additional slice to the metric for

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geographical area, so that employees can only view data related to a specific region. The result is a single metric with two slices, whose refresh returns different data depending on the activity and geographical location of the employee.

Sliced metrics allow users to drill down on individual segments of data, providing them with a more detailed look at the data that interests them.

Access restrictions on sliced metrics

Dimensions can be associated with specific user profiles so that users can only view certain slices of data. This could be useful in an extranet situation, or when different departments in a company need to see different slices of a specific metric by product line, or region, for example.

Related Topics

• Editing the user association of a dimension on page 96

Where are dimensions defined?

Sliced metric dimensions

Before you create a sliced metric, you must define dimensions in the metric universe using Designer. When you create a sliced metric by applying a dimension to a metric, the total value of the metric is calculated, as well as an individual value for each slice (for each dimension value).

Tip:

For information on defining dimensions on universes, see the Designer documentation available at: http://support.businessobjects.com/documenta

tion.

When a sliced metric is calculated, two SQL statements are executed:

• a statement for the total value of all slices of the metric

• a statement that includes a GROUP BY statement based on the dimension

that returns a distinct result for each slice, for each value of the dimension object

For example, if you create a dimension object for product line on the Revenue metric, refreshing the metric executes one SQL statement to calculate total revenue, and one SQL statement with a GROUP BY statement on the product line object, resulting in the display of revenue for each product line.

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Sliced metric dimensions

The slice values are written to the Performance Manager repository:

Information stored about sliced dimensionsRepository table

ci_probe_dim

ci_probe_dim_val ue

ci_probe_val ue

Note:

Since values are returned for each slice and stored in the Performance Manager repository, Business Objects does not recommend creating a sliced metric on a dimension with a large number of distinct values.

A dimension for use on a metric is typically built using two dimensions defined in the universe:

• dimension code: a short name used for the GROUP BY clause and joins

• dimension description: the long name used in displaying the slice

stores the name and description of the sliced dimension.

stores the list of slices generated for the dimension. Each row returned corresponds to an individual slice and is allocated an ID. An additional row is returned whose ID is 0 and whose value corresponds to the all value of the metric.

stores the actual value of the metric for each distinct slice for the defined time period.

Note:

No row is created for a slice that returns no data.

Creating a dimension

Before you define a dimension, you must:

• Create a dimension object on the metric universe in Designer. See the

Designer documentation.

• Save and export the metric universe. See the Designer documentation.

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Sliced metric dimensions

• Update the metric universe in Dashboard and Analytics Setup > System

Setup > Universes tab. See the information on metric universes in the

Dashboard and Analytics Setup documentation.

Note:

1. Go to Dashboard and Analytics Setup > System Setup > Dimensions.

2. Click Add.

3. In the Create Dimension panel, type a name for the new dimension.

4. To define a sliced metric for this dimension, click Yes, I want to create

sliced metrics on this dimension and select objects.

5. Click Next.

6. If the dimension has a sliced metric, click Refresh to list all the slices in

your dimension, then Next.

The slice names and slice codes are listed. You can also change the title of the dimension in this panel.

7. Select a dimension association and click Next.

When you create a dimension, you are creating an association for the dimension that dictates which users can access the slices or personale the content of an analytic.

Related Topics

• Configuring a dimension association on page 92

• Sliced metrics for a dimension on page 91

Sliced metrics for a dimension

To configure a dimension using a sliced metric:

1. In Dashboard and Analytics Setup > System Setup > Dimensions,

click Add.

2. In the "Create Dimension" panel, click Yes, I want to create sliced

metrics on this dimension.

3. Select a data source from the "Subject Area" list.

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4. Select the universe object to use for the dimension name from the "Object

for dimension name" list.

This name is typically a long name that helps you identify the individual slices.

5. Select the universe object to use for the dimension code from the "Object

for dimension code" list.

This object is typically a numeric key or shortened name used for the group by and joins.

6. In the "Global slice name" text box, type a name that refers to the set of

all slices of the metric.

For example, if you are slicing on regions, you name the global slice All Regions.

Related Topics

• Creating a dimension on page 90

Configuring a dimension association

An association dictates which users can access which slices. You can use an association to personalize the content of an analytic (to show only the data that interests the user) or to secure sliced metrics (by limiting the data that different users or groups of users can access).

1. Go to Dashboard and Analytics Setup > System Setup > Dimensions.

2. Click Add.

3. In the "Create Dimension" panel, define the dimension name.

4. Click Next.

Note:

If you are using a sliced metric for the dimension, you first refresh the sliced metrics and then you are asked to select the association.

5. Select one of the available association types and Click Next.

• Select None for now if you want to create slices and associate them

to users at a later time.

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Note:

You can use this option only if the dimension is based on a sliced metric.

• Select Manually, by importing users from the Business Objects

repository to search for users in the repository.

• Select Read from a database to import users from a Business Objects

universe.

Related Topics

• Sliced metrics for a dimension on page 91

• Creating a dimension on page 90

Importing users from a universe to secure dimension

This process shows you how to import users from a universe to create an association on a dimension.

1. Go to Dashboard and Analytics Setup > System Setup > Dimensions.

2. Click Add to create a dimension.

3. In the "Create Dimension" panel, you define the dimension name, click

Next.

4. Select Read from a database and click Next.

5. Select the universe containing user information from the list.

If necessary, click Refresh to refresh the list of available databases.

Sliced metric dimensions

6. From the "Object for User Name" list, select the universe object (the

database column) that contains the user name.

7. From the "Object for Dimension Name" list, select the universe object to

use for defining the dimension name.

8. From the "Object for Dimension Code" list, select the universe object to

use for defining the dimension code.

9. Do one of the following:

• Click End to confirm the user import from a universe.

• Click Previous to return to earlier screens.

• Click Cancel to cancel the dimension creation.

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Sliced metric dimensions

Manually importing users from the Business Objects repository to secure dimensions

This process shows you how to manually import users to create an association on a dimension.

1. Go to Dashboard and Analytics Setup > System Setup > Dimensions.

2. Click Add to create a dimension.

3. In the "Create Dimension" panel, you define the dimension name, click

Next.

4. Select Manually, by importing users from the Business Objects

repository and click Next.

5. If you did not activate Yes, I want to create sliced metrics on this

dimension in the first Create Dimension panel, you can provide a list

of slices to use with the association. Click Add and enter the slice name and code. You can also edit existing

slices in the list by clicking Edit Slice. When you finish selecting slices, click Next.

6. To select the users who only have limited access to the dimension, enter

character strings into the "Search" text box and click Go.

7. From the "Available Users" list, select the users for which you want to

create an association, and use the arrows to enter them into the list of "Selected User"s.

8. Click Next.

9. If you want slices for a user in the "Available Users" list, select the user

and activate Visible next to the slice name. You need to do this action for each user. Activate Select All Values to

check the visible box for all slices.

Note:

The global slice counts as a separate slice.

10. For each user in "Available Users" list, identify the default slice by

activating Default.

11. Do one of the following:

• Click End to confirm the manual user import.

• Click Previous to return to earlier screens.

• Click Cancel to cancel the dimension creation.

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Editing a dimension

You can edit the definition of a dimension, or simply edit the user association of a dimension.

1. Go to Dashboard and Analytics Setup > System Setup > Dimensions.

2. Select a dimension from the list and click Edit.

The Update Dimension window appears.

3. Optioinally, you can modify the dimension name and the global slice

name. All other boxes are grayed out.

4. Click Next.

5. Optionally, click Refresh to list all the slices in a dimension, or change

the name of the dimension.

The slice name sand slice codes are listed.

6. Click Next.

In the next screen, you have the option of editing the association defined for the dimension. An association dictates which people can access which slices. Use an association to personalize the content of an analytic, or to secure sliced metrics by limiting the data that different users or groups can access.

Performance Manager Setup and Administration Online Help

Sliced metric dimensions

7. Choose an association option.

8. Do one of the following:

• Click End.

• Click Previous to return to earlier screens.

• Click Cancel to cancel the dimension edit.

Related Topics

• Editing the user association of a dimension on page 96

• Configuring a dimension association on page 92

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Editing the user association of a dimension

If you did not define an association when you created the dimension, you can edit the association later.

1. Go to Dashboard and Analytics Setup > System Setup > Dimensions.

2. Select the dimension from the list of available dimensions.

The dimension's current associations are listed in the bottom pane (if you did not define associations for the dimension, this pane is empty). The pane displays the user associated to each slice, and the slice name and slice code of the slice to which the user is associated.

3. Choose an association option:

4. Do one of the following:

• Click End.

• Click Previous to return to earlier screens.

• Click Cancel to cancel the dimension edit.

Related Topics

• Configuring a dimension association on page 92

Removing a dimension

1. Go to Dashboard and Analytics Setup > System Setup > Dimensions.

2. Select the dimension from the list.

3. Click Remove.

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Analytics calendars

Applying a secured dimension to a data source

For each data source subject you can choose a dimension to use for individual security.

Individual security enables you to limit what users see based on a specific dimension. Once you create dimensions, you can select a dimension for each data source on which you want to apply Individual security. The dimension you select, along with its associations, are applied as the secured dimension of the data source, and dictate which data individual users can access.

1. Go to Dashboard and Analytics Setup > System Setup > Dimensions.

2. Click Individual Security Setup at the bottom of the page.

The "Individual Security" window appears.

3. In the "Subject" pane, select the data source on which you want to apply

a secured dimension.

The available dimensions for the selected data source are listed in the "Secured Dimension" pane.

4. Select the dimension with which you want to secure the data source.

5. Click OK.

Sliced metrics

Once you have created dimensions, you can slice metrics on them.

To create a sliced metric, go to Performance Manager > Metrics .

Analytics calendars

Most metrics are measured against a timeline, so you must create calendars against which you can calculate metric values. You can create the calendars based on the following types of periods:

• calendar periods

• custom periods

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Analytics calendars

• imported periods

Calendars created on this page are used to create and calculate metrics, sets and control charts. Calendars are stored in the Performance Manager repository. The calendar name is stored in the ci_series table and the calendar's definition (its dates and periods) are stored in the ci_period table.

Calendar properties

Use the "Calendar Properties" panel to define the first day of the week or year and to specify whether weekend days are included in the calendar definitions. Calendar properties apply to all calendars you create.

Go to Dashboard and Analytics Setup > Time Config and click Options. The Calendar Properties panel appears.

Note:

If no calendars have been created, all fields are blank. Once a calendar is created, the properties cannot be modified.

The "Calendar Properties" panel contains the following options:

• First day of the week

Select the day on which to start the weekly grain period. For example, if the review period is Wednesday to Tuesday, define a week as beginning on Wednesday.

• First week of the year

Select the first week of the calendar year. Define the first week of the year as the week in which January first falls, or the first week whose days are all in January.

• Weekend days

Select the days that the calendar skips systematically as weekend days.

Note:

Once you have defined calendars based on the calendar properties, the options cannot be changed. You can edit the calendar properties if no calendars rely on them.

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Calendar granularity

A calendar's granularity is the scale on which the periods are defined. Granularity is said to be fine if the detail is low-level.

Daily is the lowest possible level of granularity, therefore the shortest time span on which a calendar can be based.

Adding a calendar

Before you create calendars, you need to define the calendar properties that apply to all your calendars.

1. In Dashboard and Analytics Setup > Time Config > Calendar, click

Add.

The "Add a Calendar" window appears.

2. In the "Name" section, enter a name, and optionally, a description of the

calendar. The name of the calendar is stored in the Performance Manager repository

ci_series table.

Performance Manager Setup and Administration Online Help

Analytics calendars

3. In the "Type of periods" section, select one of the following:

• Calendar to support calendar periods.

If you select "Calendar", select an interval and specify the beginning and end dates.

• Custom to support custom periods.

• Imported to support imported periods.

4. If you select "Calendar" or "Custom", configure the calendar span.

5. Select the period display.

6. Click OK to save the calendar.

Creating a custom period calendar

Custom periods are non-standard, but consistent blocks of time, like every

3.5 weeks, every eight months, every four days.

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Analytics calendars

1. Go to Dashboard and Analytics Setup > Time Config > Calendar.

2. Click Add.

The "Add a Calendar" window appears.

3. Select Custom.

4. Type a number corresponding to the size of the interval.

For example, 1 for every day or every month, 2 for every other week, 3 for every three weeks.

5. Select an interval type.

6. Optionally, activate Skip weekend days if your custom calendar omits

Saturdays and Sundays.

7. Optionally, activate Skip, then define the days off by clicking days off, if

the custom calendar omits specific days. If you activate days off, the "Selected days off" panel appears. Select

the days to omit from the calendar, and click Add to include them in the list of days off. The days off you indicated are stored in the ci_days_off table in the Performance Manager repository.

8. Return to the topic "Adding a Calendar" to finish the calendar.

Related Topics

• Adding a calendar on page 99

• Analytics calendars on page 97

• Calendar span on page 103

Importing a calendar

Imported periods can be non-standard and inconsistent blocks of time. You can import a calendar stored in a .csv file. Only the following analytics support custom calendars: speedometers, traffic lights and interactive metric trends.

1. Go to Dashboard and Analytics Setup > Time Config > Calendar.

2. Click Add.

The "Add a Calendar" window appears.

3. Select Imported.

4. Do one of the following:

• Click Browse next to the "Document" text box to navigate to a csv

file.

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Business objects PERFORMANCE MANAGER XI 3.0 User Manual

Specifications and Main Features

Frequently Asked Questions

User Manual

Contents

Audience

Performance Manager Administrator's Guide

High-level overview

Database configuration and tuning

Dashboard and Analytics repository

Metric domain (CI_ prefix)

Performance Manager domain (IPM_ prefix)

Set Domain (SET_ prefix)

Standard options for servers

Changing the services startup parameters on UNIX

Changing the services startup parameters on UNIX

Metric Universes

Universe overview

Metric universe overview

Multiple metric universes

Creating a Basic Enterprise Metric

Enterprise metrics

Creating the universe on a target fact table

Creating a measure

Creating a measure object

Definition of a filter

Defining a filter

Exporting the universe

Dimension table filters

Pre-selecting aggregate functions and measure parameter passing

Complexities of the self-join

Date lookups

Dimensions and slicing metrics

Set-based Metrics

Set-based metrics

Design principles and SET_SET_DETAIL[C/D]

Creating set-based metrics

Using Filter objects in Set-based metrics

Defining members for a snapshot set

Defining membership for a time-based set

Creating the universe for set-based metrics

Using Filter objects in Set-based metrics

Defining members for a snapshot set

Defining membership for a time-based set

Insight into subsets

Members

Joiners

Stayers

Leavers

Types of subsets

Members

Joiners

Stayers

Leavers

Using multiple fact tables

Multiple set subject areas

Advanced Topics

Metrics on metrics

Metrics functions in the rules engine

Configuring universes for process control charts

Performance Manager Setup and Administration Online Help

Dashboard and analytic applications

What is Dashboard Builder?

What is Performance Manager?

What is Predictive Analysis?

Deployment of Dashboard and Analytics tools to your organization

What is Process Analysis?

What is Set Analysis?

Performance Manager servers

Performance Manager server options

Setting mail parameters for Dashboard and Analytics applications

Specifying web parameters for Dashboard and Analytics applications

General parameters for Dashboard and Analytics applications

Specifying general parameters in Dashboard and Analytics Setup

Specifying scheduler parameters for Dashboard and Analytics applications

Specifying database parameters for Dashboard and Analytics applications

Server caching parameters

Modifying a cache refresh or clean-up period

Dashboard and Analytics launch errors

Verifying the Dashboard and Analytics servers