DataFlux dfPower Studio Overview - DQDFPS
This course is designed for Data Quality Stewards who need an overview of the DataFlux dfPower Studio.
3 days -  Classroom |
Learn how to
- profile data
- improve data by applying various data cleansing techniques, by integration and by address verification
- control the data cleansing cycle by using trend analysis and business rules monitoring
- set up batch schedules
- define and use macro variables
- define and use custom metrics.
Who should attend?
Data Quality Stewards
Prerequisites
There are no prerequisites for this course.
Course Contents
Introduction to DataFlux and DataFlux Methodology
dfPower Studio Overview
- installation and architecture of DataFlux products
- dfPower Studio Navigator
- additional components, elements, and data access information
DataFlux Methodology: Analyse Phase
- what is metadata/data profiling?
- metadata profiling with dfPower explorer
- data profiling with dfPower profile
Introduction to dfPower Architect
- what is dfPower architect?
- working with dfPower architect
DataFlux Methodology: Improve Phase - Quality
- overview of quality techniques
- details of quality techniques
DataFlux Methodology: Improve Phase - Integration
- overview of integration techniques
- details of integration techniques
DataFlux Methodology: Improve Phase - Enrichment
- overview of enrichment techniques
- details of enrichment techniques
DataFlux Methodology: Control Phase
- overview of control phase
- trend analysis and alerts
- business rule monitoring
Doing More with dfPower Studio
- working with additional dfPower architect nodes
- defining batch schedules
- working with macro variables
- working with custom metrics
Software Addressed
This course addresses the following software product(s): DFX.
