This document provides an overview of IBM WebSphere DataStage and QualityStage version 8.0.1. It discusses key concepts in data warehousing and ETL using DataStage such as dimensional modeling, fact tables, slowly changing dimensions, and DataStage job components. It also compares server jobs to parallel jobs, and partitioning techniques. Finally, it introduces QualityStage and its data quality stages for standardizing, matching, and deduplicating data.

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Datastage (Parallel jobs & server jobs)
DATAWAREHOUSING CONCEPTS
Introduction to Data Warehousing
What is Data Warehousing?
Types of Systems
OLTP,OLAP
Data Warehousing Life Cycle
Data Warehousing Architecture
Source, Integration Layer, Staging Area
Target
Analysis & Reporting
ODS
Dimensional Modeling
What is dimension modeling?
Difference between ER modeling and dimension modeling
What is a Dimension?
What is a Fact?
Start Schema
Snow Flake Schema
Difference between Star and snow flake schema
Fact Table, Different types of facts
Fact less Fact Table
Dimensional Tables
Confirmed Dimensions, Unconfirmed Dimensions, Junk Dimensions, Degenerative
Dimensions
What are slowly changing Dimensions? Different types of SCD’s
IBM WEBSPHERE DATA STAGE AND QUALITY STAGE VERSION 8.0.1
Contents
Introduction about Data Stage
Difference between Data Stage 7.5.2 and 8.0.1
What’s new in Data Stage 8.1?
What is way ahead in Data Stage?
IBM Information Sever architecture
Datastage within the IBM Information Server architecture
Difference between Server Jobs and Parallel Jobs
Difference between Pipeline Parallelism and Partition Parallelism
Partition techniques (Round Robin, Random,
Hash, Entire, Same, Modules, Range, DB2, Auto)
Configuration File
Difference between SMP/PMP(Cluster) Architecture
Data stage components (Server components /Client components)
Designer
Introduction about Designer
Repository, Palette
Type of Links
File Stages
Sequential file
Dataset file
File set
Lookup file set
Difference between Sequential file/Dataset/File set
Overview of iWay, Classic federation and netezza
Database Stages
Dynamic RDBMS

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Oracle Enterprise
ODBC Enterprise
Stored Procedure
Processing Stages
Change Capture
Compare Stage
Difference Stage
Aggregate Stage
Transformer Stage
Difference between basic transformer and transformer
Surrogate Generator Stage
Join Stage
Merge Stage
Lookup Stage
Difference between Join/Lookup/Merge
Difference between Join/Lookup
Remove Duplicates
Switch
Pivot
Modify
Funnel
Generic stage
Different types of sorting and sort stage.
Different types of combining and collecting techniques.
Filter, External filter
Difference between filter, External filter and switch stages.
SCD stage
Encode and decode stages
FTP stage
Adding job parameters to a job, Parameter set
Difference between partitioning and re partitioning
Run time column propagation
Schema files
Debugging Stage
Head, Tail, PeaK
Row Generator
Column Generator
Sample
Containers
Difference between Local Container and Shared Container
Local Container
Shared Container
Job Sequencers
Arrange job activities in sequencer
Triggers in Sequencer
Notification activity, Terminator Activity, Wait for file activity
Start loop activity , Execute command activity
Nested Condition activity, Routine activity
Exception handing activity, User variable activity, End loop activity
Adding Checkpoints
Data stage Director
Introduction to Data stage Director
Job Status View, View logs, Scheduling
Batches Creation
Cleaning resources using Administrator
Web sphere Manager in Designer
Introduction about Data stage Manager
Importing the Job, Exporting the Job

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Importing Table Definition
Different types of table definitions and their differences.
Importing Flat File Definition
Routines
Dataset management and ORCHADMIN
Quick search and Advanced search
Data stage Administrator
Creating project, Editing project and Deleting project
Permissions to user
Different kinds of variables in Data Stage
Cleaning resources using Administrator
Web sphere Quality Stage
What is Date Quality and why do we for data quality?
Integration of Data Quality in Data Stage?
Data stage Quality stages
Investigate stage, Standardize stage Match Frequency stage
Unduplicate Match stage, Reference Match stage, Survive stage
Standardized rule sets.
Components of Standardized rule sets.