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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.

Course Contents:

Introduction to DataFlux Methodolgy and Course Flow

  • introduction
  • 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

Software Addressed

This course addresses DataFlux Data Management Studio software.

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