DataFlux Data Management Studio: Basics - DQ22DMP1
This course is for data quality stewards who perform data management tasks, such as data quality improvements, data enrichment and entity resolution.
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|3 days - Classroom|
Learn how to
- 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?
Data Quality Stewards
There are no prerequisites for this course.
Introduction to DataFlux Methodolgy and Course Flow
- course flow
Getting Started with DataFlux Data Management Studio
Working Through the PLAN Phase of the DataFlux Methodology
- creating data collections
- designing data explorations
- creating data profiles
- designing standardization schemes
Working Through the ACT Phase of the DataFlux Methodology
- introduce data jobs
- work with data quality nodes including Standardization, Identification Analysis, Right-Fielding, Parsing and Change Case
- work with data enrichment nodes including Address Verification (US/Canada) and Geocoding (self-study)
- work with entity resolution nodes including Match Codes, Clustering and Surviving Record Identification nodes
- examine multi-input/multi-output data jobs
Working Through the MONITOR Phase of the DataFlux Methodology
- introduce business rules and Business Rules Manager
- use business rules in data profiling
- use business rules via tasks in data monitoring jobs
- establish and view data alerts
This course addresses DataFlux Data Management Studio software.