DataStage Fundamentals
Enterprise Edition

Duration: Four days

Objectives:

Having completed this class the student will be able to:

• use DataStage tools to construct ETL tasks using DataStage parallel jobs
• compile and execute those tasks
• construct a hierarchy of control for those tasks

Contents:

• Beginning DataStage - What DataStage is, how it works, what it is not
• Architectures - Design-time, compile-time and run-time
• Developer's Toolkit - Introduction to the client tools that a developer uses
• Parallelism Concepts - pipeline and partition parallelism and how each is implemented in parallel jobs
• Configuration - how parallel execution is controlled
• Repository Manager - metadata creation, import, export and management
• Creating a Job - standard, structured technique for constructing a DataStage job
• Designer - editing jobs, job parameters, stages, links and their properties
• Data Sets and File Sets - parallel data storage; creation, use and management
• Director - execution and inspection/review tool
• Sequential Files - processing data in text files of various kinds
• Combining Data - horizontal combination (lookup, join, merge, funnel) and vertical combination (aggregation)
• Transforming Data - Modify and Transformer stage types
• Accessing Tables - Enterprise, API and bulk loader stage types
• Job Sequences - using a GUI to construct control hierarchies