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

The self-study e-learning includes:

• Annotatable course notes in PDF format.
• Virtual Lab time to practice.

• create and review data explorations
• create and review data profiles
• create data jobs for data improvement
• establish monitoring aspects for your data.

Kinek ajánljuk

Elérhető képzési formák	Időtartam
Tantermi:	3.0 nap
e-Learning:	21 óra/180 nap licensz

There are no prerequisites for this course.

A tanfolyam DataFlux Data Management Studio szoftver használatára épül.

This course addresses DataFlux Data Management Studio 2.6 and DataFlux Data Management Server 2.6.

• 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 Managment 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
• woriking with the Data Management server