Unit – 9: Advanced Stages in Parallel Jobs (Version 8.1)
DIFFERENCE BETWEEN DATASTAGE 7.5 AND 8.1 GENERATOR
Head – Tail – Peek – Column generator – Row generator –Write RangeMap Stage.ĪBAP Stage,IDoc Extract Stage,IDoc Load Stage, BAPI stage Sequential file – Dataset – File set – Lookup file set.Ĭopy – 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. Unit – 8: Working with Parallel Job Stages Introduction to Datastage Designer – Importance of Parallelism – Pipeline Parallelism – Partition Parallelism – Partitioning and collecting – Symmetric Multi Pro9cessing (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. 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 – 4 : Introduction to Datastage Version 7.5x2 & 8.1ĭatastage introduction – IBM information Server architecture – DataStage components – DataStage main functions – Client components.ĭatastage 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.
Introduction to Extraction, Transformation & Loading- Types of ETL Tools – Key tools in the market. Introduction to Data Modeling – Entity Relationship model (E-R model) – Data Modeling for Data Warehouse, Narmalization process – Dimensions and fact tables – Star Schema and Snowflake Schemas. IBM WebSphere DataStage and QualityStage 8.1Īn 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.
Home Training Courses Data Warehousing - Data Stage