Placement Assistance IBM Infosphere DataStage Training

Placement Assistance IBM Infosphere DataStage Training institute

IBM Infosphere DataStage and QualityStage 9.1
Unit -1: Data Warehouse Fundamentals
An introduction to Data Warehousing – purpose of Data Warehouse – Data Warehouse Architecture – Operational Data Store – OLTP Vs Warehouse Applications – Data Marts- Data marts Vs Data Warehouses – Data Warehouse Life cycle .
Unit -2: Data Modelling
Introduction to Data Modeling – Entity Relationship model (E-R model) – Data Modeling for Data Warehouse, Normalization process – Dimensions and fact tables – Star Schema and Snowflake Schemas.
Unit -3: ETL Design Process
Introduction to Extraction, Transformation & Loading- Types of ETL Tools – Key tools in the market.
Unit – 4 : Introduction to Datastage Version 7.5x2 & 8.5
Datastage introduction – IBM information Server architecture – DataStage components – DataStage main functions – Client components.
Unit – 5 : Datastage Administrator
Datastage project Administration - Editing projects and Adding Projects – Deleting projects Cleansing up project files – Enviranmental Variables–Environement management – Auto purging – Rutime Column Propagation(RCP) – Add checkpoints for sequencer – NLS configuration – Generated OSH (Orchestra Engine) – System formats like data, timestamp – Project protect – Version details.
Unit – 6: Datastage Director
Introduction to Datastage Director – Validating Datastage Jobs – Executing Datastage jobs – Job execution status – Monitoring a job – Job log view – job scheduling – Creating Batches – Scheduling batches.
Unit – 7 : Datastage Designer
Introduction to Datastage Designer – Importance of Parallelism – Pipeline Parallelism – Partition Parallelism – Partitioning and collecting – Symmetric Multi Processing (SMP) Massively Parallel Processing (MPP) – Partition techniques – Datastage Repository Palette – Passive and Active stages – Job design overview – Designer work area – Annotations – Creating jobs –
Importing flat file definitions – Managing the Metadata environment – Dataset management – Deletion of Dataset – Routines – Arguments.
Unit – 8: Working with Parallel Job Stages
Database Stages
Oracle – Teradata – ODBC – dynamic RDBMS
File Stages
Sequential file – Dataset – File set – Lookup file set.
Processing Stages
Copy – Filter – Funnel – Sort Remove duplicate – Aggregator – Modify – Compress – Expand – Decode – Encode – Switch – Pivot stage – Lookup – Join – Merge – difference between look up, join and merge – change capture – Change apply – Compare – Difference – Surrogate key generator – Transformer.
Debug Stages

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