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
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)
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
Sede | Data | P | ||
---|---|---|---|---|
Roma | 02/12/2019 | |||
Milano | 03/02/2020 | |||
Bologna | 02/03/2020 | |||
Roma | 20/04/2020 | |||
Bologna | 18/05/2020 | |||
Milano | 14/09/2020 | |||
Roma | 14/09/2020 |