Overview

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.

Audience

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

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)

Objective

Please refer to the course overview

Course Outline

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