This course introduces SAS Data Integration Studio and includes topics for registering sources and targets; creating and working with jobs; and working with transformations.

The self-study version of this course includes structured course notes that provide a detailed overview, essential skills, and exercises, along with a software Virtual Lab to practice.

The e-learning includes:

• digital course notes for self-study
• Virtual Lab: 30 hours of hands-on software practice.

This course can help prepare you for the following certification exam(s): SAS Data Integration Development for SAS 9.

Learn how to

• register source data and target tables
• create jobs and explore the functionality of the job editor
• work with many of the various transformations.

Who should attend
Data integration developers and data integration architects

Formats available	Standard duration
Classroom:	3.0 days
e-Learning:	15 hours/ 30 days	System Requirements

Before attending this course, you should have experience with SAS programming basics. You can gain this experience by completing the SAS Programmation 1: L'essentiel course.

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

• exploring the platform for SAS Business Analytics
• introduction to the data management applications
• introduction to the classroom environment and the course tasks

• introduction to change management
• establishing a change management environment (self-study)

• setting up the environment
• registering source data metadata

• registering target data metadata
• importing metadata

• introduction to jobs and the job editor
• using the Join transformation

• defining and loading the customer dimension table
• defining and loading the organization dimension table
• defining and loading the time dimension table

• importing SAS code
• propagation and mapping
• chaining jobs
• performance statistics
• metadata reports

• introduction
• using the Extract and Summary Statistics transformations
• exploring SQL transformations
• establishing status handling
• using the Data Validation transformation
• using the Transpose, Sort, Append, Rank, and List Data transformations
• basic standardizations