IBM InfoSphere DataStage Essentials V8.7 Training

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  • Project Based Learning
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IBM InfoSphere DataStage Essentials V8.7 Training Course Overview

IBM InfoSphere DataStage Essentials V8.7 training lays emphasis on the process of building and running DataStageExtract, Transform and Load (ETL) tasks. It covers how DataStage fits in IBM information server architecture. With the help of live demos the participants will learn how to read and write data available in various formats from different sources, including relational tables, data sets, and sequential files. The training also explains how to conduct different types of processing over data, namely sorting, aggregating, data filtering, data combining, and business transformations.

On the completion of the training you will inculcate the following skills:

  • Describe DataStage uses and workflow
  • Understand the Information Server architecture, Information Server Web Console, and the DataStage parallel processing architecture
  • Describe the DataStage deployment options and the DataStage Administrator client to create/configure DataStage users
  • Design, compile, run, and monitor DataStage parallel jobs
  • Use the DataStage Transformer stage to Implement complex business logic
  • Use the DataStage PX Debugger to debug DataStage jobs
  • Use DataStage ODBC and DB2 Connector stages  to read and write to database tables
  • Determines the profitability of using FastTrack and Metadata Workbench with DataStage
Target audience

Professionals such as ETL developers and Project administrators, who are responsible for data extractions and transformations using DataStage.

Prerequisites
  • Knowledge of Windows operating system
  • Conceptual fundamentals of database access techniques
  • Familiarity with  Open Database Connectivity (ODBC) 

IBM InfoSphere DataStage Essentials V8.7 Training Course Content

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

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