There is a new version of this course. Please see SAS Data Integration Studio: Essentials.
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 e-learning includes:
- Annotatable course notes in PDF format.
- Virtual Lab time to practice.
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 | Duration | | |
Classroom: |
3.0 days | | |
|
Before attending this course, you should have experience with SAS programming basics. You can gain this experience by completing the SAS Programming 1: Essentials course.
This course addresses SAS Data Integration Studio, SAS Analytics Platform software.
Introduction- exploring the platform for SAS Business Analytics
- introduction to the data management applications
- introduction to the classroom environment and the course tasks
Working with Change Management- introduction to change management
- establishing a change management environment (self-study)
Creating Metadata for Source Data- setting up the environment
- registering source data metadata
Creating Metadata for Target Data- registering target data metadata
- importing metadata
Creating Metadata for Jobs- introduction to jobs and the job editor
- using the Join transformation
Orion Star Case Study- defining and loading the customer dimension table
- defining and loading the organization dimension table
- defining and loading the time dimension table
Additional Features for Jobs- importing SAS code
- propagation and mapping
- chaining jobs
- performance statistics
- metadata reports
Working with Transformations- 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