InfoSphere DataStage holds an IBM ETL Tool that stays on apart from Information Platforms Solutions. DataStage is recognized for using any Graphical representation as building data integration clarifications. DataStage acceptation used within organizations to work because of an interface between practices. Among DataStage stages with examples, individual users can extract, translate and load the data from a source over each target.

DataStage is available into three versions, Enterprise (PX), Server and VMS editions. Here result was first acquainted with the industry by VMark which held next won over with IBM

Who Should Take This Course?

DataStage became bright future. It holds an IBM Tool. DataStage implies an ETL Tool that adopts as graphical documentation as a number of data. Best companies are those career hiring ETL Developer. The average pay of Datastage ETL Developer is approximately $ 1,193,00. The audience can go to this idea:

 Data Analyst

 Fresher’s (who are looking they career in Business Intelligence).

 Software Developers

What Are The Prerequisites?

Basic Knowledge upon Databases can help. SQL is benefited easily not mandatory. Other than none specific requirements exist not required. Each trainer will advise you on the basics and support these are needed DataStage basics concepts.

Hands-On Experience:

Our 24*7 expert's club will support covers Real-time Projects. Each trainer can support to guide learners work out a proper level like mindfulness toward the course DataStage training material for free. This is grateful to servings on details trainer at the functional assignments DataStage tutorial.




  • Introduction to Data Warehousing

      • What is Data Warehousing?Who needs Data Warehousing?
      • Why is Data Warehouse required?
      • Data Warehousing Architecture
      • Types of Systems
      • OLTP
      • OLAP
      • Data Warehousing Life Cycle
      • ODS
      • Data Marts
      • Types of Data Marts
      • Staging Area

    Data Modelling Concepts

      • Data Modelling Types
      • Source
      • Integration Layer
      • Target

    Multi-Dimensional Data Modelling Concepts

      • What is dimension data modeling?
      • Difference between ER modeling and dimension modeling
      • What is a Dimension?
      • Different Types of Dimension
      • Confirmed Dimensions
      • Junk Dimensions
      • Degenerate Dimensions
      • Slowly Changing Dimensions Types
      • What is a Fact?
      • Fact Types, Classification of Facts?
      • Factless Fact Table
      • Different Schema Types
      • Star Schema
      • Snow Flake Schema
      • Difference between Star and snowflake schema

    IBM DataStage Tool:

    IBM DataStage Contents

      • Introduction to Data Stage
      • DataStage architecture
      • Difference between Server Jobs and Parallel Jobs
      • Difference between Pipeline Parallelism and Partition Parallelism
      • Partition techniques
      • Configuration File
      • Difference between SMP/MPP Architecture
      • Data stage Client Components
      • Data stage Server Components

    DataStage Administrator

      • Introduction about Administrator
      • Project creation and project properties setup

    DataStage 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

    Database Stages

      • Dynamic RDBMS
      • Oracle Connector
      • ODBC Enterprise

    Processing Stages

      • Aggregate Stage
      • Transformer Stage
      • Surrogate Generator Stage
      • Join Stage
      • Merge Stage
      • Lookup Stage
      • Difference between join/Lookup/Merge
      • Difference between join/Lookup
      • Remove Duplicates
      • Switch
      • Pivot
      • Modify
      • Funnel
      • 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.
      • Change Capture stage
      • Slowly Changing Dimension stage
      • Job Parameters & Parameter set
      • Runtime column propagation
      • Sequencer Jobs

    Debugging Stage

      • Head
      • Tail
      • Pea
      • Row Generator
      • Column Generator
      • Sample

    DataStage Director

      • Introduction to Data stage Director
      • Job Status View
      • View logs
      • Scheduling.


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