IBM InfoSphere DataStage v11.5 Advanced Data Processing KM423G

2 days


This course is designed to introduce you to advanced parallel job data processing techniques in DataStage v11.5. In this course you will develop data techniques for processing different types of complex data resources including relational data, unstructured data (Excel spreadsheets), and XML data. In addition, you will learn advanced techniques for processing data, including techniques for masking data and techniques for validating data using data rules. Finally, you will learn techniques for updating data in a star schema data warehouse using the DataStage SCD (Slowly Changing Dimensions) stage. Even if you are not working with all of these specific types of data, you will benefit from this course by learning advanced DataStage job design techniques, techniques that go beyond those utilized in the DataStage Essentials course.


Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek techniques for working with complex types of data resources.

Skills Gained

  • Use Connector stages to read from and write to database tables
  • Handle SQL errors in Connector stages
  • Use Connector stages with multiple input links
  • Use the File Connector stage to access Hadoop HDFS data
  • Optimize jobs that write to database tables
  • Use the Unstructured Data stage to extract data from Excel spreadsheets
  • Use the Data Masking stage to mask sensitive data processed within a DataStage job
  • Use the Hierarchical stage to parse, compose, and transform XML data
  • Use the Schema Library Manager to import and manage XML schemas
  • Use the Data Rules stage to validate fields of data within a DataStage job
  • Create custom data rules for validating data
  • Design a job that processes a star schema data warehouse with Type 1 and Type 2 slowly changing dimensions


DataStage Essentials course or equivalent.

Course Outline

  • Unit 1 –Accessing databases
  • Topic 1: Connector stage overview
  • Topic 2: Connector stage functionality
  • Topic 3: Error handling in Connector stages
  • Topic 4: Multiple input links
  • Topic 5: File Connector stage
  • Demonstration 1: Handling database errors
  • Demonstration 2: Parallel jobs with multiple Connector input links
  • Demonstration 3: Using the File Connector stage to read and write HDFS files
  • Unit 2 – Processing unstructured data
  • Topic 1: Using the Unstructured Data stage in DataStage jobs
  • Demonstration 1: Processing unstructured data
  • Unit 3 – Data masking
  • Topic 1: Using the Data Masking stage in DataStage jobs
  • Demonstration 1: Data masking
  • Unit 4 – Using data rules
  • Topic 1: Introduction to data rules
  • Topic 2: Use the Data Rules stage to valid foreign key references in source data
  • Topic 3: Create custom data rules
  • Demonstration 1: Using data rules
  • Unit 5 – Processing XML data
  • Topic 1: Introduction to the Hierarchical stage
  • Topic 2: Composing XML data
  • Topic 3: Writing Hierarchical data to a relational table
  • Topic 4: Using the Regroup step
  • Topic 5: Consuming XML data
  • Topic 6: Transforming XML data
  • Demonstration 1: Importing XML schemas
  • Demonstration 2: Compose hierarchical data
  • Demonstration 3: Consume hierarchical data
  • Demonstration 4: Transform hierarchical data
  • Unit 6: Updating a star schema database
  • Topic 1: Surrogate keys
  • Topic 2: Slowly Changing Dimensions (SCD) stage
  • Demonstration 1: Build a parallel job that updates a star schema database with two dimensions

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