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The tool provides full integration facilities to the file servers like Linux, UNIX, Hadoop and well proven scripting languages like SHELL, PERL etc. Also, it provides separate interface for web-based java and even chains web service and XML.

  • End-to-end coverage
  • Practical exposure
  • Live assignments
  • Maximum Hands – on training
  • Complete support
  • Post Training Support
  • Pre and Post Test/Evaluation
  • Special content Customization if needed
  • Global Certification coverage
  • Global Certification Vouchers – Discounted
  • Certification preparation
Datastage Introduction
  • Datastage Architecture
  • Datastage Clients
  • Designer
  • Director
  • Administrator
  • Datastage Workflow
Types of Datastage Job
  • Parallel Jobs
  • Server Jobs
  • Job Sequences
Setting up Datastage Environment
  • Datastage Administrator Properties
  • Defining Environment Variables
  • Importing Table Definitions
Creating Parallel Jobs
  • Design a simple Parallel job in Designer
  • Compile your job
  • Run your job in Director
  • View the job log
  • Command Line Interface (dsjob)
Accessing Sequential Data
  • Sequential File stage
  • Data Set stage
  • Complex Flat File stage
  • Create jobs that read from and write to sequential files
  • Read from multiple files using file patterns
  • Use multiple readers
  • Null handling in Sequential File Stage
Platform Architecture
  • Describe parallel processing architecture Describe pipeline & partition parallelism
  • List and describe partitioning and collecting algorithms
  • Describe configuration files
  • Explain OSH & Score
Combining Data
  • Combine data using the Lookup stage
  • Combine data using merge stage
  • Combine data using the Join stage
  • Combine data using the Funnel stage
Sorting and Aggregating Data
  • Sort data using in-stage sorts and Sort stage
  • Combine data using Aggregator stage
  • Remove Duplicates stage
Transforming Data
  • Understand ways Datastage allows you to transform data
  • Create column derivations using userdefined code and system functions
  • Filter records based on business criteria
  • Control data flow based on data conditions
Repository Functions
  • Perform a simple Find
  • Perform an Advanced Find Perform an impact analysis
  • Compare the differences between two Table Definitions and Jobs.
Working with Relational Data
  • Import Table Definitions for relational tables.
  • Create Data Connections.
  • Use Connector stages in a job.
  • Use SQL Builder to define SQL Select statements.
  • Use SQL Builder to define SQL Insert and Update statements.
  • Use the DB2 Enterprise stage.
Metadata in Parallel Framework:
  • Explain schemas.
  • Create schemas.
  • Explain Runtime Column Propagation (RCP).
  • Build a job that reads data from a sequential file using a schema.
  • Build a shared container.
Job Control
  • Use the Datastage Job Sequencer to build a job that controls a sequence of jobs.
  • Use Sequencer links and stages to control the sequence a set of jobs run in.
  • Use Sequencer triggers and stages to control the conditions under which jobs run.
  • Pass information in job parameters from the master controlling job to the controlled jobs.
  • Define user variables.
  • Enable restart.
  • Handle errors and exceptions.