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DATASTAGE COURSE – LEARN @ YOUR CONVENIENCE

Unit – 1: Data Warehouse Fundamentals

    1. An Introduction to Data Warehousing
    2. Purpose of Data warehouse
    3. Data Warehouse Architecture
    4. Operational Data Store
    5. OLTP Vs Warehouse Applications
    6. Data Marts
    7. Data marts Vs Data Warehouses
    8. Data warehouse Life cycle
    9. Metadata management.

Unit – 2: Data Modelling

    1. Introduction to Data Modelling
    2. Entity Relationship model(E-R model)
    3. Data Modeling for Data Warehouse
    4. Dimensions and fact tables
    5. Star Schema and Snowflake Schemas
    6. Coverage Tables
    7. Fact less

Unit – 3: ETL Design process

    1. Introduction to Extraction, Transformation & Loading
    2. Types of ETL Tools
    3. What to look for in ETL Tools
    4. Key tools in the market
    5. ETL Trends & New Solution Options.

Unit – 4: Data stage installation

    1. Datastage Installation
    2. Prerequisites to install Datastage
    3. Installation process.

Unit – 5: Introduction to Data stage version

    1. Datastage Introduction
    2. IBM Information Server architecture
    3. DataStage within the IBM Information Server architecture
    4. Datastage components
    5. DataStage main functions
    6. Client components.

Unit – 6: Datastage Administrator

    1. Datastage project Administration
    2. Editing projects and Adding projects
    3. Deleting projects
    4. Global variable setting
    5. Environment management
    6. Runtime Column Propagation (RCP)
    7. Enable Remote Execution of Parallel jobs
    8. Add checkpoints for sequencer
    9. NLS configuration

Unit – 7: Datastage Director

    1. Introduction to Datastage Director
    2. Validating Datastage Jobs
    3. Executing Datastage jobs
    4. Job execution status
    5. Monitoring a job
    6. Job log view
    7. Job scheduling.-
    8. Message Handler Management
    9. Multiple job compile

Unit 8: Datastage Designer

    1. Introduction to Datastage Designer
    2. Importance of Parallelism
    3. Pipeline Parallelism
    4. Partition Parallelism
    5. Partitioning and collecting
    6. Symmetric Multi Processing (SMP)
    7. Massively Parallel Processing (MPP)
    8. Partition techniques
    9. Datastage Repository
    10. Palette –
    11. Passive and Active stages
    12. Job design overview
    13. Designer work area
    14. Annotations
    15. Creating jobs, deleting jobs
    16. Parameter passing
    17. Compiling jobs
    18. Batch compiling
    19. Validating jobs
    20. Importing flat file definitions
    21. Managing the Metadata environment
    22. Dataset management
    23. Deletion of Dataset
    24. Parameter sets

Unit 9: Working with Parallel job stages.

    1. Database stages
    2. Oracle
    3. DB2
    4. Teradata
    5. ODBC
    6. Sql Server stage.
    7. File stagesSequential file
    8. Dataset
    9. Processing stages
    10. Copy
    11. Filter
    12. Funnel
    13. Sort
    14. Remove duplicate
    15. Aggregator
    16. Modify
    17. Pivot stage
    18. Lookup
    19. Join
    20. Merge
    21. Difference between look up, join and merge
    22. Change capture
    23. Change apply
    24. Surrogate key generator
    25. Transformer.
    26. Debug stages
    27. Head
    28. Tail
    29. Peek
    30. Column generator
    31. Row generator
    32. Restructure stages
    33. column export
    34. column import

Unit 10: Advanced stages in Parallel jobs (Version 8.0.1)

    1. Range Lookup process
    2. Surrogate key generator stage
    3. Slowly changing dimension stage
    4. Job performance analysis
    5. Slowly Changing Dimensions implementation
    6. Performance tuning.

Unit 11: Job Sequencers

    1. Arrange job activities in Sequencer
    2. Triggers in Sequencer
    3. Restability
    4. Recoverability
    5. Notification activity
    6. Terminator activity
    7. Wait for file activity
    8. Execute Command activity
    9. Nested Condition activity
    10. Routine activity
    11. Exception handling activity
    12. User Variable activity
    13. End Loop activity

Unit 12: WebSphere Quality Stage

    1. About Data Quality
    2. Datastage Quality stages
    3. Investigate stage
    4. Standardize stage
    5. Unduplicated Match stage