Detailed Course Outline
1. Data Quality Issues • Listing the common data quality contaminants • Describing data quality processes
2. QualityStage Overview • Describing QualityStage architecture • Describing QualityStage clients and their functions
3. Developing with QualityStage • Importing metadata • Building DataStage/QualityStage Jobs • Running jobs • Reviewing results
4. Investigate • Building Investigate jobs • Using Character Discrete, Concatenate, and Word Investigations to analyze data fields • Reviewing results
5. Standardize • Describing the Standardize stage • Identifying Rule Sets • Building jobs using the Standardize stage • Interpreting standardize results • Investigating unhandled data and patterns
6. Match • Building a QualityStage job to identify matching records • Applying multiple Match passes to increase efficiency • Interpreting and improving Match results
7. Survive • Building a QualityStage survive job that will consolidate matched records into a single master record
8. Two-Source Match • Building a QualityStage job to match data using a reference match