Data Quality Using DataFlux Technology: Fast Track - DQFT
This intensive training course provides accelerated learning for those students who need to have a better understanding of DataFlux and data management concepts and methodology. Students will have an extensive overview of dfPower Studio and architecture; improving quality, integration, and enrichment; the DataFlux Integration Server; introduction to dfPower Customise; QKB components; data types and definitions; remote job processing; and real time services. This course is for individuals who are comfortable with learning large amounts of information in a short period of time. Other data quality courses are available to provide the same type of information in a much more detailed approach over a longer period of time.
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Duration
5 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
- configure the DataFlux Integration Server
- process jobs remotely
- establish real time services
- understand the QKB components
- use the QKB component editors
- understand various definition types.
Who should attend?
Data Quality Stewards
Prerequisites
There are no prerequisites for this course.
Course Contents:
Introduction to DataFlux and Data Management Concepts
dfPower Studio Overview
- installation and architecture of DataFlux products
- dfPower Studio interface
- understand 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
- standardisation
- other data cleansing techniques
DataFlux Methodology: Improve Phase - Integration
- overview of integration techniques
- details of integration techniques
- matching techniques
DataFlux Methodology: Improve Phase - Enrichment
- overview of enrichment techniques
- details of enrichment techniques
- address verification
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 (self-study)
- working with macro variables (self-study)
- working with custom metrics (self-study)
Introduction to DataFlux Integration Server
- examples using DataFlux Integration Server
- configuration
Remote Job Processing
- remotely submitting a dfPower Architect job
- uploading jobs to the DataFlux Integration Server
- executing on another DataFlux Integration Server
Real Time Services
- creating a service
- creating a service on generic input data
- interacting with services
Introduction to QKB Customisation
- introduction
- understand the structure of the QKB
- investigate the component editors
Definitions
- parse definitions
- match definitions
- standardised definitions
Other Definitions
- case definitions
- gender analysis definitions
- identification definitions
- pattern analysis definitions
Software Addressed
This course addresses the following software product(s): DFX.
