cognos10 for beginner's part iii

Creating Sales Analysis ModelCognos 10 BI Framework Manager

Beginner’s Guide Part II

Provided By: BISP Created By: Mitesh Agrawalhttp://bispsolutions.wordpress.com Reviewed By: Amit Sharma http://learncognosreports.wordpress.com/ Team BISP

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Cognos 10 BI Framework Manager Beginner’s Guide Part I| http://learncognosreports.wordpress.com | BISP

This is another document from “Cognos for Beginner’s” Series. The documents briefs about basic of Cognos Framework Manager and the steps to build the Data Model for Sales Analysis reports in Framework manager. Join our professional training program to learn from the experts.

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Table of Contents Overview of Framework Manager………………………………………..………...4 Introduction to Framework Manager…………………………………….…………5 Planning Your Metadata……………………………………………...…………….7 Contents of Framework Manager ……………………………………….…………8

o Project ……………………………………………………………….9o Metadata Model………………………………………………………10o Namespaces……………………………………………………………11o Data Sources…………………………………………………………...12o Query Subject…………………………………………………..………13o Query Item……………………………………………………………..14o Relationship…………………………………………………….……...15o Package………………………………………………………..……….16

Architecture to Framework Manager………………………………………………..17 Design and create Project……………………………………………………………18 Create a project…………………………………………………….………………..19 Framework Manager : View………………………………………..……………….32

o Physical View……………………………………………………………32o Business View…………………………………………………………..37o Presentation View……………………………………………………….46

Create Relationship……………………………………………………………..……50 Adding Business Rules in Framework Manager…………….....….…………..…..52 Modeling Relational Metadata…………………………………………….………….60 Creating Dimension Objects For OLAP- Style Reporting………………….........66

o Create a Regular Dimension………………………….….……….……66o Create a Measure Dimension………………………..….……………..84

Create and Publish Package……………………………………….....……….……..87 Validation to Data Model………………………………………………..………….….94 Apply Security in IBM Cognos Framework Manager……………….…………..…100


Adding Business Rules in Framework Manage: Business rules are used to refine retrieved data and to ensure that the right information is available for report authors.

It can be added to dimensions and query subjects in a model to refine data.

It can be maintained centrally so that all reports are updated automatically as the rules evolve.

Using business rules we can add calculations, filters, prompts and session parameters.

Benefits of business rules:

It saves times as we do not have to re-create them as and when required.

It ensures consistency as user use the same definition.

Easy to update, as it is maintained centrally and is updated automatically.

It enhance security, e.g. filters can be applied to limit the data that user see.

Adding Calculated column to data model-

In Framework Manager we can add a calculated column to provide report authors with calculated values for regular use.

Open a model to which a new calculated column has to be added.

If a stand-alone calculation has to be added, click model folder.

Go to Measure table create Query Item.


New Calculation Definition windows appears, provide a ‘Name’ for the new calculated column

Define the expression-

Drag and drop items which are required to define the expression from the available pane.

We are creating the calculated column, which uses the total member function to show the total revenue.

To test the expression, click ‘test’ button.


If no errors are found in expression, it will display the ‘Result’.

A new column (i.e; calculated column) appears in the model.


Adding Filters to Data Model:

A filter returns a Boolean value so that rows are returned by a dimension and query subject can be limited.

Framework Manager supports stand-alone filters and embedded filters.

Use stand-alone filter to reuse the expression.

Use a embedded filter to use a filter with only one dimension or query subject.

Steps to create a filter-

Double click on any dimension.

Query Subject Definition window appears, In this window click Filter tab.


Click ‘Add’ button in the bottom of the Query Subject Definition window to create a Filter.

Filter Definition window appears. In the name box, provide a ‘Name’ to the filter and click blue arrow.


After clicking on blue arrow, we need to define expression in Expression definition box and click ‘Ok’ .

The Dimension or Query Subject Definition window will appears, this windows shows, filter is added.


Click on ‘Test’ tab, then select ‘Test Sample’ button.

After click on ‘Test Sample’, you can see the Test Results and Press ‘Ok’.


Modeling Relational Metadata

After importing metadata, you must ensure that it is set up to meet your user’s reporting requirement.

We recommend that you create at least two views:

Import view/ Physical view

Business view

Import view/ Physical view- The Import view/ Physical view contains the metadata you imported from the data sources.

To ensure that the metadata is set up correctly in the import view/physical view, do the following-

Ensure that the relationships reflect the reporting requirements.

Optimize and customize the data retrieved by query subjects.

Optimize and customize the data retrieved by dimensions.

Control how data is used and formatted by checking query item properties.

Business view- The business view provides a layer to the information in the source data so that it is easier for users to build reports.


To enhance the metadata in the business view, do the following-

Add business rules, such as calculations and filters that define the information users can retrieve.

Organize the model by creating separate views for each user group that reflects the business concepts familiar to end users.

In the modeling relational metadata, you will interact with following objects:

Data Model

Dimensions.

Dimension Hierarchy.

Facts /Measures

Facts/Measures-

Measure/Facts are the key performance indicator that you want to evaluate .To determine which of the numbers in the data might be measures. A rule of thumb is: If number makes sense when it is aggregated, then it is a measure.

A measure/facts can: provide quantifiable results that gauge the success of your business. address primarily numeric questions. add perspective to your data.

Data Model –

Data model is a method used to define and analyze data requirements needed to support the business processes of an organization.

Data modeling defines data elements, their structures and relationships between them.

Data modeling is also a technique for detailing business requirements for a database.

• Using Data Modeling, you can manage data as a resource; the integration of information systems designing databases/data warehouses (data repositories).

Types of Data Model:

Physical Data Model:

Physical data model represents how the model will be built in the database.


http://en.wikipedia.org/wiki/Database

http://en.wikipedia.org/wiki/Requirement

http://en.wikipedia.org/wiki/Business_process

http://en.wikipedia.org/wiki/Requirement

http://en.wikipedia.org/wiki/Software_development_process

A physical database model shows all table structures, including column name, column data type, column constraints, primary key, foreign key, and relationships between tables.

Features of a physical data model:

Specification all tables and columns. Foreign keys are used to identify relationships between tables. Demoralization may occur based on user requirements. Physical considerations may cause the physical data model to be quite different from the logical data model.

Logical Data Model:

Logical data models represent the abstract structure of some domain of information. A logical data model describes the data in as much detail.

Features of a logical data model:

• Includes all entities and relationships among them. • All attributes for each entity are specified. • The primary key for each entity is specified. • Foreign keys (keys identifying the relationship between different entities) are specified. • Normalization occurs at this level.

Dimensions-

A dimension is a broad grouping of data about a major aspect of a business, such as products, dates and markets. Dimensions are the categories of data analysis. Dimension represents the highest level of data. Levels represent a logical hierarchy of that data. Dimensions are arranged in hierarchical levels, with unique positions within each level.

Types of Dimensions-

Regular Dimension Measure Dimension

Regular Dimension –


A regular dimension contains descriptive and business key information and organizes the information in a hierarchy, from the highest level of granularity to the lowest. It usually has multiple levels and each level requires a key and a caption. If you do not have a single key for your level, it is recommended that you create one in a calculation. Model regular dimensions are based on data source or model query subjects that are already defined in the model.

When creating regular dimensions, you must understand the dimensionality of the data. You must be able to answer the following questions :

What are the levels in your dimension? What is the order and combination of levels that form hierarchies? What are the relationships between the levels? What uniquely identifies a level? Which data elements are associated at each level? Are foreign keys defined in the data source?

Measure Dimension –

A measure dimension is a collection of facts. You can create a measure dimension for one or more query subjects that have a valid relationship between them. Model measure dimensions should be composed of only quantitative items. Only measures are visible in the model measure dimension. Query items, such as keys, are hidden. You can add value by embedding calculations based on existing business rules, such as Profit Margin. You can change the order of measures, query items, and calculations.

For example, in a project for sales analysis, you include this dimensions:


Name Type Description

Time Regular dimension Dates of sales organized into years, quarters,

Months, weeks, and days when sales were made.

Market Regular dimension Locations of sales grouped into sales regions,

district and areas.

Product Regular dimension Product details organized by product type,

brand, size, color, and description.

Customer Regular dimension Customer, segment information

Sales Measure dimension Purchase details such as units sold, revenue, and Profit.

Dimension Hierarchy –

Dimension hierarchies occur when different structural views can be applied to the same data. Depending on the nature of the hierarchies and the required reports, you may need to evaluate the modeling technique.

Each dimension in a data warehouse may have one or more hierarchies applied to it.

The Time Dimensional Hierarchy will be appear as-

Year

Half

Quarter

Month

Week

Day

The Market Dimensional Hierarchy will be appear as-

Region

District

Area

Market Detail


Create Dimension Objects for OLAP-style Reporting :To Create Dimension Objects for OLAP- style Reporting, we need to do-

Create Regular Dimension Create Measure Dimension

Steps to create Regular Dimension-

Right click on Physical View CreateNamespace

Specify a Name (as Dimension View) to a New Namespace.

Right click on Dimension ViewCreateRegular Dimension then Dimension Definition window will appear.


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In the Available Items Pane, expand the Business ViewD0 Time

After expand the D0 Time then drag Year( i.e; Per_Name_Year) into the Hierarchy Pane.


Right Click the Top Per_Name_Year in the Hierarchy Column and then Rename it by type Time. Similarly Rename Per_Name_Year(All) to Time(All) and Bottom Per_Name_Year to Year.

The Result will be display as shown in figure.


We need to assign a business key and member caption to each level. In the Hierarchy pane Right click on Year level in the bottom pane then click Edit Roles.

For Specify Roles Click a business key and press ‘Close’.


Press ‘Add ‘ in bottom right corner of Hierarchy pane..

Create Dimension Objects for OLAP-style Reporting

Calculation Definition window will appear. Specify the Name in the box and expand the business view then select the Year ( i.e; Per_Name_Year) from Available Components and click blue arrow.


We can view Year column in the Expression Definition box.

Edit the expression in the Expression Definition Box and click on Test Button to view the result.


We can view the Result in the Calculation definition window.

We can view the Year and Year Caption in the bottom level of Hierarchy Pane.


In the Hierarchy pane Right click on Year Caption level in the bottom pane then click Edit Roles.

For Specify Roles Click a member Caption and press ‘Close’.


The Year level now has business key and member caption assigned in the bottom level of Hierarchy pane.

Similarly From the Available Items Pane drag the Half (i.e; Per_Name_Half) under the Year level in the Hierarchy Pane.


In the Hierarchy pane Right click on Year level in the bottom pane then click Edit Roles.

For specify Roles ,Click business key and then ‘close’.


Press ‘Add ‘ in bottom right corner of Hierarchy pane..

Calculation Definition window will appear. Specify the Name in the box and expand the business view then select the Half ( i.e; Per_Name_Half) from Available Components and click blue arrow.


Edit the expression in the Expression Definition Box and click on Test Button to view the result. The Results display in the Test Result box of the Calculation Definition window.

In the Hierarchy pane Right click on Half Caption level in the bottom pane then click Edit Roles.


To Specify Roles click on member caption and press close.

The Half level now has business key and member caption assigned in the bottom level of Hierarchy pane.


Similarly we can drag the all required Query Items From the Available Items Pane and drop it in the Hierarchy Pane. The Time Hierarchy is shown in the below window.

Click the Member sort tab on the Dimension Definition window..


Under Sorting Options , Select Metadata, Data and Always (OLAP Compatible).

Drag an Year Item from select a level to assign Sort Properties pane and drop it Available Data Items Pane and Select a Year business key from Available Data Items Pane and Press Green arrow.


We can view the Year business key in the Level Sort Properties pane to sort the data. In this case the business keys for the levels are used.

Similarly Drag an Day Item from select a level to assign Sort Properties Pane and drop it Available Data Items Pane and Select a Day business key from Available Data Items Pane and Press Green arrow.


We can view the Day business key in the Level Sort Properties pane to sort the data and click ‘Ok’.

Now Rename the New Dimension to Time.


The Time Dimension is complete and now expand the Time Dimension in the Project Viewer, the following Items will display.

Similarly we can create more Regular Dimension according to Business Requirement.

Steps to create a Measure Dimension-

Right Click on Dimension viewCreateMeasure Dimension.


Dimension Definition window will appear. Drag Measure items from Model Object Pane and drop it in Measures pane.

Click ‘Test ‘Button.


Press Test sample Button to see ‘Test Result’ and Press ‘Ok’.

For View the Query Information, click on Query Information. Cognos SQL and Native SQL will be appear on Dimension Definition Window and Press ‘Ok’.


Create and Publish Package

Steps to Create a Package--

Right click on packagecreatepackage, for create a new package.


Give the Name to the package, here description of the package and screen tip are optional, then press ‘Next’ button.

Here you can check and uncheck the objects, which you want to include in the package from the project . Press ‘Next’ after the selection.

In this window, you will select the set of function that is available in the package, Although we are using a SQL Server so here we will select SQL Server as set of functions .


After selecting the set of functions, you will press ’Finish’ Button.

Your package have been successfully created. Now press ’Yes’ for open the Publish Package Wizard otherwise press ’No’.


By default it will show you Package Wizard Location, try to keep it same and Press ‘Next’.

In this window, you have to add the security privileges to the packages, which type of user can access the package ,then press the ’Add’ button.


In next screen,you have the folder name (cognos), which you have created, now double click on it then you have the list of Users and group of user who can view the package.

Select the user by click on check box , then press the green arrow.


After press on green arrow , selected users will move in the selected entries block , then press ‘OK’.

You can view the group of user, who have a privileges to access the package, then press ‘Next’.


Verify the package before publishing it , now press ‘Publish’ to publish the package.

You have successfully published the package , now click on ‘Exit this wizard’ and press ‘Finish’.


Validation to Data Model

For validating to data model, Go to the following link-

http://localhost:9300/p2pd/servlet/dispatch

The following screen will appear. Firstly we need to go

Public FolderssamplesModels Created Package Name ( Package which you have created previously). This is a Package where report will be stored.

Go to Launch Analysis studio. Basically Analysis Studio is used for OLAP (Online Analytical Processing) Reporting.

By default the Cross Tab window will appear, now expand the Dimension View and simply drag the items from the Insertable Object and drop it in the middle pane.


http://localhost:9300/p2pd/servlet/dispatch

Now drag the Time(All) from the Insertable Object and drop it in the Row box , drag the Market(All) from the Insertable Object and drop it in the Column box and drag the Revenue from the Insertable Object and drop it in the Measure Box. The window will appear as given below.

Click on Test Button to Run the Report. In my case the Report will be appear on HTML page.


The Time Dimensional Hierarchy will be appear as-

Year

Half

Quarter

Month

Week

The Market Dimensional Hierarchy will be appear as-

Region

District

Area

Market Detail

We can view the Time Dimensional Hierarchy for all the Market as shown in below screens step by step-


cognos10 for beginner's part iii

Documents

member caption assigned

day business key

calculation definition window

click blue arrow

modeling relational metadata

time dimensional hierarchy

dimension definition window

logical data model