Moyens d'évaluation :
- Quiz pré-formation de vérification des connaissances (si applicable)
- Évaluations formatives pendant la formation, à travers les travaux pratiques réalisés sur les labs à l’issue de chaque module, QCM, mises en situation…
- Complétion par chaque participant d’un questionnaire et/ou questionnaire de positionnement en amont et à l’issue de la formation pour validation de l’acquisition des compétences
Who should attend
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)
Course Content
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.
Moyens Pédagogiques :