This course will step you through the QualityStage data cleansing process. You will transform an unstructured data source into a format suitable for loading into an existing data target. You will cleanse the source data by building a customer [...]
  • KM413G
  • Délka 4 dny
  • 0 ITK bodů
  • 0 termínů
  • Praha (49 300 Kč)

    Brno (49 300 Kč)

    Bratislava (1 972 €)

This course will step you through the QualityStage data cleansing process. You will transform an unstructured data source into a format suitable for loading into an existing data target. You will cleanse the source data by building a customer rule set that you create and use that rule set to standardize the data. You will next build a reference match to relate the cleansed source data to the existing target data.

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The intended audience for this course are:

  • QualityStage programmers
  • Data Analysts responsible for data quality using QualityStage
  • Data Quality Architects
  • Data Cleansing Developers
  • Data Quality Developers needing to customize QualityStage rule sets

This course will step you through the QualityStage data cleansing process. You will transform an unstructured data source into a format suitable for loading into an existing data target. You will cleanse the source data by building a customer rule set that you create and use that rule set to standardize the data. You will next build a reference match to relate the cleansed source data to the existing target data.

Participants should have:

  • Compled the QualityStage Essentials course, or have equivalent experience
  • familiarity with Windows and a text editor
  • familiarity with elementary statistics and probability concepts (desirable but not essential)
  • Modify rule sets
  • Build custom rule sets
  • Standardize data using the custom rule set
  • Perform a reference match using standardized data and a reference data set
  • Use advanced techniques to refine a Two-source match
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