There is a newer version of this course. Please see the schedule for the new DataFlux Data Management Studio: Essentials course.
This course is for data quality stewards who perform data management tasks, such as data quality improvements, data enrichment and entity resolution.
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 currently are no prerequisites for this course.
This course addresses DataFlux Data Management Studio software.This course addresses DataFlux Data Management Studio 2.4 and DataFlux Data Management Server 2.4.
Introduction to DataFlux Methodolgy and Course Flow
Getting Started with DataFlux Data Management Studio
- introduce Data Management Platform architecture
- introduce DataFlux Data Management methodology
- review course flow and topics
Working Through the PLAN Phase of the DataFlux Methodology
- explore the basics of the DataFlux Data Management Studio interface
- create a DataFlux Data Management Studio repository
- work with data connections
Working Through the ACT Phase of the DataFlux Methodology
- create data collections
- design data explorations
- create data profiles
- design standardization schemes
Working Through the MONITOR 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
Exploring Additional Topics
- introduce business rules and Business Rules Manager
- use business rules in data profiling
- establish and view data alerts
- work with data monitoring nodes including execute business rule and data monitoring nodes
- work with data jobs with multiple inputs and multiple outputs
- work with data job references within a data job
- introduce DataFlux Data Management Server
- work through a cumulative case study (self-study)