This 30-hour online course covers implementing extract, transform, and load (ETL) solutions using IBM DataStage. Students will learn about DataStage fundamentals, ETL strategies, data transformation rules, data quality checks, business rules, data loading techniques, and optimized ETL solutions. The course materials include a student guide, lab guide, and case studies. Topics covered include DataStage architecture, components, administration, job design, debugging stages, and containers.

1. IBM DataStage : Implementing ETL Solution using IBM DataStage
Course Description:
This course covers the basic of Data Warehousing fundamentals, ETL Fundamentals and focuses on implementing
Extract, Transform and Load strategy using IBM DataStage. Learn the real work Data Transformation rules, Data Quality
Check, Basic and Advance Business Rules, Data Loading Strategies and optimized ETL solutions. The training is full of real
time case studies, Problem/Solutions based model and based on current job requirements.
Course Duration: 30 hours.
Take Away: Student Guide, Lab Guide and Case Studies.
Class Delivery: On-Line (Interactive Web Based )
Contents
 Introduction about Data Stage
 Difference between Server Jobs and Parallel Jobs
 Difference between Pipeline Parallelisms
 Partition techniques (Round Robin, Random, Hash, Entire, Same, Modules,Range,DB2,Auto)
 Configuration File
 Difference between SMP/MPD architecture
 Data Stage Components (Server components/Client Components)
 Package Installer
Data Stage Administrator
 Creating project, Editing project and Deleting project
 Permissions to user
 .Apt Config file
 Environment variable creation, permission
Data stage director
 Introduction to Data stage Director
 Job status View
 View logs
 Scheduling
 Batches Creation
Designer
 Introduction about Designer
 Repository
 Palatte
 Types of Links
 File Stages
 Sequential File
 Data set File
 Lookup file set
 Difference between Sequential file/Dataset/File set
 Database stages
 Dynamic RDBMS
 Oracle Enterprise
 ODBC Enterprise
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2.  Stored Procedure
Processing stages
 Change Capture (Caption)
 Compare stage
 Difference Stage
 Aggregate Stage
 Transformer Stage
 Surrogate Generator Stage
 Join Generator Stage
 Merge Generator Stage
 Lookup Generator Stage
 Difference between join/Lookup/Merge
 Difference between join/Lookup
 Remove Duplicates
 Switch
 Pivot
 Modify
 Funnel
Debugging stage
 Head
 Tail
 Pea
 Row Generator
 Column Generator
 Sample
 Job Parameters
Manager
 Introduction About Data stage Manager
 Importing the Job
 Exporting the Job
 Importing Table Definition
 Importing Flat File Definition
 Routines
Containers
 Difference between Local Container and Shared Container
 Local Container
 Shared Container
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