This course introduces SAS Data Integration Studio and includes topics about change management, registering source data and target data in metadata, creating and working with jobs, and working with transformations. The course also provides information about creating iterative processes, creating conditional processes, defining new transformations, in-database processing, analyzing metadata, promoting metadata, versioning metadata, and deploying jobs.

The self-paced e-learning includes:

• Annotatable course notes in PDF format.
• Virtual lab time to practice.

Learn how to

• View a sample job.
• Work with change management.
• Create metadata for source data, target data, and jobs.
• Work with propagation and mapping in jobs.
• Establish status handling in jobs.
• Work with various transformations (data, SQL, analysis).
• Create iterative processes with the Loop and Loop End transformations.
• Create conditional processes with the Conditional Start and Conditional End transformations.
• Create custom transformations.
• Work with the Table Loader transformation.
• Process in-database.
• Analyze metadata using impact and reverse impact analysis.
• Promote metadata.
• Version metadata by creating archives.
• Deploy jobs for scheduling.

Who should attend

Data integration developers and data integration architects

Formats available	Standard Duration (duration can vary, see event schedule for details)
Classroom:	4 days
Live Web Classroom:	8 half-day session(s)
e-Learning:	28 hours/180 day license

Before attending this course, you should have experience with the following:

• SAS programming basics.
• SQL processing.
• SAS macro facility.

You can gain this experience by completing the SAS Programming 1: Essentials, SAS SQL 1: Essentials, and SAS Macro Language 1: Essentials courses.

This course addresses SAS Data Integration Studio, SAS Data Quality Solution, SAS Analytics Platform software.

Getting Started with SAS Data Integration Studio

• Introduction to SAS Data Integration Studio.
• Exploring the course environment.
• Viewing a sample job.
• Working with change management.

Creating Metadata for Source Data

• Registering SAS libraries.
• Registering SAS table metadata.
• Registering DBMS table metadata.
• Registering ODBC data source table metadata.
• Registering metadata for external files.

Creating Metadata for Target Data

• Registering target data metadata.
• Importing metadata.

Creating Metadata for Jobs

• Creating jobs.
• Using transformations.
• Working with the Join transformation.

Orion Star Case Study

• Creating the star schema.

Additional Features for Jobs

• Working with propagation and mappings.
• Establishing status handling for transformations and jobs.

Working with Transformations

• Using data transformations.
• Using SQL transformations.
• Using analysis transformations.

Creating Iterative Processes

• Introduction to iterative processing.
• Creating the control table.
• Creating the parameterized job.
• Creating the iterative job.

Creating Conditional Processes

• Using control transformations.
• Creating a conditional process.

Creating Custom Transformations

• Working with transformation templates.
• Creating custom transformations.
• Using custom transformations.

Working with the Table Loader Transformation

• Introduction to table loader transformations.
• Exploring load styles.
• Managing indexes and constraints.

Working with Databases

• Introduction to in-database processing.
• Using in-database processing.
• Exploring processing techniques.

Analyzing, Promoting, and Versioning Metadata

• Analyzing metadata using impact analysis.
• Promoting metadata.
• Versioning metadata.

Deploying Jobs

• Introduction to deployment.
• Deploying and scheduling jobs.