IBM Cognos Data Manager – Build Data Marts with Enterprise Data (V10.2)

The IBM Cognos Data Manager: Build Data Marts with Enterprise Data (V10.2) course is intended for developers.

You should have:

• a knowledge of basic Windows functionality, database and dimensional analysis concepts, as well as a working knowledge of SQL

Getting Started

• Identify the purpose of IBM Cognos Data Manager
• Define data warehousing and its key underlying concepts
• Identify how Data Manager creates data warehouses
• Examine the Data Manager architecture and user interface

Create a Catalog

• Examine the purpose and contents of Data Manager catalogs
• Create a catalog
• Define connections to source and target data
• Access data using SQLTerm
• Configure flat data source files using SQLTXT

Create Hierarchies

• Examine the role of the dimensional framework in Data Manager
• Examine hierarchies and their data sources
• Identify how to create hierarchies from the columns of one table, the rows of one table, and from multiple tables
• Test and view hierarchies
• Create a hierarchy of static date values
• Handle weeks in a date hierarchy

Create Basic Builds

• Examine Data Manager builds and build-related terminology
• Create a dimension build using the Dimension Build wizard
• Create a fact build using the Fact Build wizard
• Test and execute a fact build
• Document a catalog
• Create catalog schema

Create Derivations

• Examine derivations
• Apply operators and functions to derivations
• Examine the derivation timing model
• Add derivations to a fact build

Create Conformed Dimensions

• Examine conformed dimensions and their advantages
• Design conformed dimensions
• Create conformed dimensions
• Create data integrity lookups that use conformed dimensions

Customise Reference Structures

• Create hierarchies manually using different approaches
• Examine the features of a hierarchy
• Examine literals
• Set data access for hierarchy levels
• Examine static and dynamic members
• Examine fostering
• Use derivations in a hierarchy

Process Dimensional History and Late Arriving Facts

• Examine slowly changing dimensions (SCDs)
• Use surrogate keys in SCDs
• Manage type 1 and type 2 changes to dimensional data
• Load historical data for a dimension
• Examine late arriving facts
• Process late arriving facts in a fact build

Transform Data Using Lookups and Derived Dimensions

• Identify when to use lookups
• Identify the requirements for a lookup
• Create a translation lookup
• Create an optional lookup
• Add derived dimensions to fact builds

Customise Data Delivery

• Configure fact and dimension delivery modules
• Create indexes on fact and dimension tables
• Update fact data using keys

Customise Fact Data Processing

• Filter fact data
• Merge duplicate fact data
• Examine fact data integrity checking
• Reject fact data

Aggregate, Filter, and Partition Fact Data

• Aggregate fact data
• Examine aggregate rules
• Vertically restrict fact data
• Horizontally restrict fact data
• Partition fact data

Implement Job Control

• Examine where job control fits into the data warehouse lifecycle
• Create a JobStream
• Add, link, and reposition nodes
• Execute a JobStream and view the results

Automate Functionality Using Commands

• Differentiate between the Command Line Interface (CLI) and Data Manager Designer
• Identify common commands
• Use commands in a batch file
• Examine variables

Customise Functionality with User-Defined Functions and Variables

• Examine user defined functions (UDFs)
• Create an internal UDF
• Create a user-defined variable

Process Unbalanced Hierarchical Data

• Examine balanced, unbalanced, and ragged hierarchies
• Add a recursive level to a hierarchy
• Identify ways to balance a hierarchy and delivered flattened data
• Examine circular references

Pivot Fact Data

• Examine pivoting
• Use the single pivot technique
• Use the advanced pivot technique
• Examine reverse pivoting

Resolve Data Quality Issues

• Identify data quality and cleansing issues
• Handle fostered and unmatched members
• Perform debugging using SQLTerm and functions
• Assess the quality of output data

Troubleshoot and Tune the Data Manager Environment

• Use build logging to ensure that data marts are being loaded properly
• Perform dimension breaking
• Manage memory and resources
• Export DDL statements

Organise and Package Data Manager Components

• Export and import components using packages
• Search for components in a catalog using Navigator

Integrate with IBM Cognos BI

• Examine IBM Cognos BI
• Identify the role of metadata dimensions, metadata collections, and metadata stars
• Export Data Manager metadata to XML
• Import Data Manager XML into Framework Manager
• Use Data Manager metadata with IBM Cognos BI
• Publish a data movement task to IBM Cognos Connection

End-to-End Workshop

Entity-Relationship Model of the GO_Demo Database (Optional)

Work in a Multi-Developer Environment (Optional)

• Examine collaborative development support
• Examine the source code repository
• Examine the component dependency model
• Identify planning considerations

Standardising Dimensions and Facts Exercise (Optional)

Review of Data Manager Essentials (Optional)

• Data warehouse design
• The purpose of Data Manager components
• Development steps in Data Manager to create data marts
• Track dimensional changes and late arriving facts

Work with SAP R/3 Data (Optional)

• Identify how to access SAP R/3 data sources using the IBM Cognos Data Manager Connector for SAP R/3 tool