SAS-DI Data Integration Studio

Overview of SAS Data Integration Studio
1
exploring the platform for SAS Business Analytics
2
reviewing the course data and course tasks
Working with Change Management
1
introduction to change management
2
establishing a change management environment (self-study)
Creating Metadata for Source Data
1
setting up the environment
2
registering source data metadata
Creating Metadata for Target Data
1
registering target data metadata
2
importing metadata for target data
Creating Metadata for Jobs
1
introduction to jobs and the job editor
2
using the SQL join transformation
Additional Features for Jobs
1
importing SAS code
2
working with propagation and mappings
3
chaining jobs
4
investigating performance statistics
Working with Transformations
1
working with the extract transformation
2
working with summary statistics transformation
3
exploring status handling for transformations and jobs
4
working with the data validation transformation
5
working with the sort transformation
6
working with the append transformation
7
working with the transpose transformation
8
working with the apply lookup standardization transformation
Working with Slowly Changing Dimensions
1
defining slowly changing dimensions
2
using the SCD Type 2 Loader and Lookup transformations
3
introducing the Change Data Capture transformations (self-study)
Working with Loop Transformations
1
introduction to Loop transformations
2
iterating a job with Loop transformations
3
iterating a single transformation with Loop transformations
Defining New Transformations
1
SAS code transformations
2
using the new transformation wizard
Working with Tables and the Table Loader Transformation
1
basics of the Table Loader transformation
2
load styles of the Table Loader transformation
3
table properties and load techniques of the Table Loader transformation
Additional Topics for SAS Data Integration Studio Users
1
overview
2
analyzing metadata using impact analysis
3
metadata promotion
4
metadata reports
5
checkpoint/restart
6
deploying jobs for scheduling
7
deploying jobs as SAS Stored Processes
Implementing Data Quality Techniques
1
SAS and data quality
2
working with the DataFlux IS transformations
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