This course is for data quality stewards who perform data management tasks such as data quality improvements, data enrichment, and entity resolution.

• Create and review data explorations.
• Create and review data profiles.
• Create data jobs for data improvement.
• Establish monitoring aspects for your data.

Who should attend

Formats available	Standard Duration (duration can vary, see event schedule for details)
Classroom:	3.0 days

There are no prerequisites for this course.

This course addresses DataFlux Data Management Studio software.

This course addresses DataFlux Data Management Studio 2.7 and DataFlux Data Management Server 2.7.

• Providing an overview of the technology offerings for SAS Data Quality.
• Discussing the DataFlux Data Management Platform architecture.

• Navigating the DataFlux Data Management Studio interface.
• Creating a Data Management Studio repository.
• Verifying the course QKB and reference sources.
• Working with data connections.

• Creating data collections.
• Designing data explorations.
• Creating data profiles.
• Designing data standardization schemes.

• Introduction to data jobs.
• Setting options for data jobs.
• Creating a simple data job.

• Identifying functionality that is available in the Quality grouping of nodes.
• Standardization, parsing, and casing
• Identification analysis and right fielding.

• Understanding the data enrichment data sources.
• Working with address verification in a data job.

• Discussing the concept of match codes.
• Describing the process of generating match codes.
• Creating match codes.
• Clustering records.
• Adding survivorship to the entity resolution job.

• Defining business rules.
• Adding a business rule and an alert to a profile.
• Creating a historical visualization.
• Using a business rule in a data job.
• Data jobs with monitoring tasks.

• Multi-input/multi-output data jobs.
• Using data job references within a data job.
• Working with the Data Management server.