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IBM WebSphere DataStage        Course Details (PDF)     

Training Hours: 40
Course Contents

  • Data Warehousing - An Overview
    • Data Warehouse Definition
    • OLTP vs OLAP
    • Data Warehouse Process Overview
    • Staging Area
    • Datamart

  • DWH – Design Concept
    • Star schema
    • Snowflake schema
    • Fact constellations

  • Data modeling techniques
    • E/R modeling
    • Dimensional modeling

  • Database design methodology for data warehouses

  • Case Study: Real time Retail industry scenario DWH design

  • Datastage tool Overview
    • Datastage Server
    • Datastage Parallel Extender
    • Comparison between Datastage Server Vs Parallel

  • Introduction to Datastage PX
    • DataStage Architecture
    • DataStage Clients
      • Designer
      • Director
      • Administrator

  • DataStage Workflow (Runtime architecture)

  • Types of DataStage Job
    • Parallel Jobs
    • Server Jobs
    • Job Sequence

  • Setting up DataStage Environment
    • DataStage Administrator Properties
    • Defining Environment Variables
    • Importing Table Definitions

  • Creating Parallel Jobs
    • Design a simple Parallel job in Designer
    • Compile your job
    • Run your job in Director
    • View the job log
    • Command Line Interface (dsjob)

  • Accessing Sequential Data
    • Sequential File stage
    • Data Set stage
    • Create jobs that read from and write to sequential files
    • Read from multiple files using file patterns
    • Use multiple readers
    • Null handling in Sequential File Stage

  • Platform Architecture
    • Describe parallel processing architecture Describe pipeline &
    • Partition parallelism
    • List and describe partitioning and collecting algorithms
    • Describe configuration files
    • Explain OSH & Score

  • Sorting and Aggregating Data
    • Sort data using in-stage sorts and Sort stage
    • Combine data using Aggregator stage
    • Remove Duplicates stage

  • Combining Data
    • Combine data using the Lookup stage
    • Combine data using merge stage
    • Combine data using the Join stage
    • Combine data using the Funnel stage

  • Transforming Data
    • Understand ways DataStage allows you to transform data
    • Create column derivations using user defined code and system functions
    • Filter records based on business criteria
    • Control data flow based on data conditions

  • Working with Relational Data
    • Import Table Definitions for relational tables.
    • Create Data Connections.
    • Use SQL Builder to define SQL Select statements.
    • Use SQL Builder to define SQL Insert and Update statements.
    • Use the DB2 Enterprise stage.

  • Metadata in Parallel Framework
    • Explain schemas.
    • Create schemas.
    • Explain Runtime Column Propagation (RCP).
    • Build a job that reads data from a sequential file using a schema

  • Job Control
    • Checkpoint/Restart
    • Looping
    • Expression Support
    • User Variables Stage
    • Automatically Handling Aborts
    • Terminator Stage ~ aborting a sequence
    • Enhanced Variable Support
    • Enhancements to other activity stages:

  • Performance tuning techniques

  • DataStage Tips and Tricks

  • Best practices overview
    • Standards
    • Development guidelines
    • Component usage
    • DataStage Data Types
    • Partitioning data
    • Collecting data
    • Sorting
    • Stage specific guidelines