IBM InfoSphere DataStage Essentials 9.1 (KM202)

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About this Course

This course is designed to introduce ETL developers to DataStage 9.1.

This is the Classroom version of Instructor-led online course IBM InfoSphere DataStage Essentials 9.1 (ILO) (3M202).

Audience Profile

This is a basic course for project administrators and ETL developers responsible for data extractions and transformations using DataStage.

At Course Completion

Upon completing this course, students will be able to:

  • Describe the uses of DataStage and the DataStage workflow
  • Describe the Information Server architecture and how DataStage fits within it
  • Describe the Information Server and DataStage deployment options
  • Use the Information Server Web Console and the DataStage Administrator client to create DataStage users and to configure the DataStage environment
  • Import and export DataStage objects to a file
  • Import table definitions for sequential files and relational tables
  • Design, compile, run, and monitor DataStage parallel jobs
  • Design jobs that read and write to sequential files
  • Describe the DataStage parallel processing architecture
  • Design jobs that combine data using joins and lookups
  • Design jobs that sort and aggregate data
  • Implement complex business logic using the DataStage Transformer stage
  • Debug DataStage jobs using the DataStage PX Debugger
  • Read and write to database tables using DataStage ODBC and DB2 Connector stages
  • Work with the Repository functions such as search and impact analysis
  • Build job sequences that controls batches of jobs
  • Understand how FastTrack and Metadata Workbench can be profitably used with DataStage

Prerequisites

You should have basic knowledge of the Windows operating system and some familiarity with database access techniques.

Course Outline

  1. Unit 1 - Introduction to DataStage
  2. Unit 2 - Deployment
  3. Unit 3 - DataStage Administration
  4. Unit 4 - Working with Metadata
  5. Unit 5 - Creating Parallel Jobs
  6. Unit 6 - Accessing Sequential Data
  7. Unit 7 - Partitioning and Collecting
  8. Unit 8 - Combining Data
  9. Unit 9 - Group Processing Stages
  10. Unit 10 - Transformer Stage
  11. Unit 11 - Repository Functions
  12. Unit 12 - Working with Relational Data
  13. Unit 13 - Job Control
  14. Unit 14 - Intersecting with Other Information Server Products