Facets Demo New Batches Starting from Saturday... 22-10-2016
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DataFlux Data Management Studio online training

DataFlux Data Management Studio Essential


DataFlux Data Management Studio(DDMS) is a data management suite that combines :Data quality, Data integration,Master data management.It provides a process and technology framework to deliver a single, accurate and consistent view of your enterprise data.Data Management Studio gives you the ability to:Merge customer, product, or other enterprise data ,Unify disparate data through a variety of data integration methods (batch, real time, virtual) ,Verify and complete address information ,Integrate disparate data sets and ensure data quality ,Transform and standardize product codes ,Monitor data for compliance in batch or real time ,Manage metadata hierarchy and visibility.


  • None.


  • It is a 12 days program and extends up to 2hrs each.
  • The format is 40% theory, 60% Hands-on.

  • It is a 3 days program and extends up to 8hrs each.
  • The format is 40% theory, 60% Hands-on.
    Private Classroom arranged on request and minimum attendies for batch is 4.

course content

  • Introduction to DataFlux Methodolgy and Course Flow
    • overview Data Management Platform architecture
    • introduce and explore DataFlux Data Management methodology
    • review course flow, topics, and data
  • Getting Started with DataFlux Data Management Studio
    • explore the basics of the DataFlux Data Management Studio interface
    • create a DataFlux Data Management Studio repository
    • discuss the Quality Knowledge Base (QKB) and reference sources
    • work with data connections
  • Working Through the PLAN Phase of the DataFlux Methodology
    • create data collections
    • design data explorations
    • create data profiles
    • design standardization schemes
  • Working Through the ACT Phase of the DataFlux Methodology
    • introduce data jobs
    • work with data quality nodes including standardization, parsing, change case, identification analysis, and right-fielding
    • 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
  • Working Through the MONITOR Phase of the DataFlux Methodology
    • introduce business rules and the Business Rules Manager
    • use business rules in data profiles
    • establish and view data alerts
    • work with data monitoring nodes including execute business rule and data monitoring


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