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Training goals

code: KM413GPL | version: v11.x

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.

Please refer to the course overview

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

Conspect Show list

After completing this course,  you should be able to:
• 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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Additional information

Prerequisites

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)
Difficulty level
Duration 3 days

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