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: Completed 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)
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
Please refer to the course overviewCloud & Data PlatformData and AIUnified Governance & Integration MarketDataOps Portfolio