SAS 9 Data Integration Fast Track

This intensive training course provides accelerated learning for those who will use SAS Data Integration processes, including data cleansing and enrichment, ETL processing, and data federation.

This course is for individuals who are comfortable with learning large amounts of information in a short period of time. The Using SAS Data Integration Studio to Build Data Marts from Enterprise Data Sources, Using SAS Data Integration Studio to Create Efficient ETL Processes, and Using the SAS Data Quality Solution to Cleanse Your Data courses are available to provide the same type of information in a more detailed approach over a longer period of time.

Duration:

5 days

Learn how to

• create data mart/data warehouse tables necessary for querying and reporting
• deploy jobs for scheduling
• maintain jobs that build tables by tracking efficiencies
• incorporate data quality standards in ETL flows
• perform maintenance of the Quality Knowledge Base
• where possible, take advantage of the SAS Scalable Performance Data Server.

Who should attend:

Data integration developers who need to learn the SAS Data Integration process in a short period of time

Prerequisites

Before attending this course you should view the free Self-Paced e-Learning module Overview: SAS Business Intelligence. You should also have some SAS programming experience. SAS programming experience can be obtained by attending the SAS Programming 1: Essentials course or viewing the Self-Paced e-Learning programming courses.

Course Contents

Introduction to SAS Data Integration Studio

• defining the SAS Intelligence Platform
• navigating in SAS Data Integration Studio

Working Under Change Management

• defining change management
• identifying repository types
• using change management

Building a Data Mart

• reviewing the case study defining the source data
• defining the target tables
• loading the target tables

Building an OLAP Cube

• defining OLAP
• building an OLAP cube
• viewing an OLAP cube

Creating Reports

• discussing reporting transformations
• building a frequency report
• creating a custom transformation
• defining a stored process
• stating the features of a stored process
• specifying tools that can use stored processes

Additional Topics and Transformations

• defining features of import and export
• defining features of the copy, paste, and paste special options
• defining features of impact analysis
• specifying attributes of the Loop transformation

Tracking Efficiency in ETL Flows: Basic Tuning

• identifying important concepts for SAS Data Integration Studio
• tracking and measuring efficiencies
• working with intermediate files
• views or physical tables for ETL flows
• transformation and column optimisation

Tracking Efficiency in ETL Flows: Data, Sorts, and Joins

• identifying additional techniques to improve performance
• working with data, sorts, and joins

SAS and Data Quality

• defining data quality
• describing the methodology of data quality
• reviewing data quality tasks

Data Profiling

• defining data profiling
• data profiling with dfPower Studio

Data Cleansing: Standardization

• defining data standardization
• standardising data with dfPower Studio
• standardising data with SAS Data Integration Studio
• standardising data with SAS

Data Cleansing: Additional Functionality

• learning additional data quality/cleansing techniques
• describing the functionality of dfPower Architect
• sequencing the steps to build a job
• describing SAS Data Quality Server functions

Data Integration

• matching and integrating data
• identifying the parts of dfPower match
• using dfPower Match and dfPower Architect to generate match codes
• describing the data integration capabilities of SAS Data Integration Studio

Software Addressed

This course addresses the following software product(s): SAS Data Integration Studio, SAS Intelligence Platform, SAS Data Quality Solution.