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DataFlux Data Management Studio: Fast Track - DQ22DMFT

This course is for data quality stewards who perform data management tasks, such as data quality, data enrichment and entity resolution. We will also learn some about the Quality Knowledge Base (QKB) and using the DataFlux Data Management Platform Customize application.

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Duration

5 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
  • working with the DataFlux Expression Engine Language
  • creating process jobs
  • using macro variables
  • creating reference jobs
  • creating custom metrics
  • understand the QKB components.

Who should attend?

Data Quality Stewards

Prerequisites

There currently are no prerequisites for this course.

Course Contents:

Introduction to DataFlux Methodolgy and Course Flow

  • introduction
  • course flow

DataFlux Data Management Studio: Getting Started

  • introduction
  • Quality Knowledge Base and reference sources
  • data connections

Working Through the PLAN Phase of the DataFlux Methodology

  • creating data collections
  • designing data explorations
  • creating data profiles
  • designing data standardisation schemes

Working Through the ACT Phase of the DataFlux Methodology

  • introduction to 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

Exploring the QKB

  • understanding the structure of the QKB
  • examine several component editors

Staging

  • overview of remaining course topics
  • establish necessary connections to data and repositories
  • activate a macro file

DataFlux Expression Engine Language (EEL)

  • introduction to DataFlux Expression Engine Language
  • data profiling using EEL
  • using the expression node: IF/ELSE statements
  • using the expression node: RETURN statement
  • using the expression node: Pushrow function (self-study)
  • using the expression node: grouping functionality (self-study)

Advanced Features

  • working with custom metrics
  • using data job references within a data job
  • working with macro variables
  • using multiple locales in a data job (self-study)

Process Jobs

  • introduction to process jobs
  • using Data Job and Data Job (reference) nodes
  • using macro variables in process jobs
  • working with Global Get/Set and Echo nodes
  • using the If Then node
  • examining event listening

Tips, Tricks, and Other Topics

  • how data is processed in a data job•
  • job optimisation (self-study)•
  • tips for building and testing jobs•
  • DataFlux Data Management server•
  • deploying jobs (self-study)•
  • promote to production

Software Addressed

This course addresses DataFlux Data Management Server, DataFlux Data Management Studio software.

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