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) (3M202GB).
You should have basic knowledge of the Windows operating system and some familiarity with database access techniques.
- Unit 1 - Introduction to DataStage
- Unit 2 - Deployment
- Unit 3 - DataStage Administration
- Unit 4 - Working with Metadata
- Unit 5 - Creating Parallel Jobs
- Unit 6 - Accessing Sequential Data
- Unit 7 - Partitioning and Collecting
- Unit 8 - Combining Data
- Unit 9 - Group Processing Stages
- Unit 10 - Transformer Stage
- Unit 11 - Repository Functions
- Unit 12 - Working with Relational Data
- Unit 13 - Job Control
- Unit 14 - Intersecting with Other Information Server Products
- 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
This is a basic course for project administrators and ETL developers responsible for data extractions and transformations using DataStage.
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