IBM Cognos Data Manager: Build Data Marts with Enterprise Data (v10.2) (B5280G) – Outline

Outline detalhado do curso

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

Customize 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

Customize Data Delivery

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

Customize 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

Customize 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

Organize 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

Standardizing 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