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Overview:

Datastage is normally used in large corporations as an interface  between their different systems which also takes care of extraction, translation and the loading to the systems. The Datastage interfaces are called jobs which can be configured in such a way that they can run on single servers as well as multiple servers in a grid architecture.


Objective:

    • DataStage provides the ability to perform extract, transform, and load (ETL) operations from multiple sources to multiple targets, including DB2 for z/OS
    • It gives developers maximum speed, flexibility and effectiveness in building, deploying, updating and managing the data integration infrastructure.
    • 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 control batches of jobs

Audience:

Project administrators and ETL developers responsible for data extraction and transformation using Data Stage.


Prerequisites:

      • Knowledge of the Windows OS.
      • Familiarity with Open Database Connectivity (ODBC) and relational database access technique.

 Technological advantages

      • It handles all company data and adapts to the needs;
      • It offers the possibility for the organization of a complex business intelligence;
      • Flexibly and scalable;
      • It accelerates the running of the project;
      • Easily implementable

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Course Curriculum

Introduction to Data warehousing
INTRODUCTION TO DATAWAREHOUSING 00:00:00
Data Modelling
Data Modelling 00:00:00
ETL Design process
ETL Design process 00:00:00
Data stage installation
Data stage installation 00:00:00
Introduction to Datastage version 8.x
Introduction to Datastage version 8.x 00:00:00
Datastage Administrator
Datastage Administrator 00:00:00
Datastage Designer
Datastage Designer 00:00:00
Datastage Director
Datastage Director 00:00:00
JOB SEQUENCER
JOB SEQUENCER 00:00:00
CONTAINERS
CONTAINERS 00:00:00
PARALLEL PROCESSING AND PARTIONING METHODS
PARALLEL PROCESSING AND PARTIONING METHODS 00:00:00
KEY SERVICE I Potential Migration approach and techniques
KEY SERVICE I Potential Migration approach and techniques 00:00:00
KEY SERVICE II
KEY SERVICE II 00:00:00

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