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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Mapping Development and Execution | 12% | - Parameters, variables, and workflow integration - Building and testing IDQ mappings - Debugging and performance tuning |
| Topic 2: Data Profiling | 20% | - Pattern discovery and data domain identification - Column and rule-based profiling - Analyzing profile results and quality metrics |
| Topic 3: Matching and Consolidation | 25% | - Comparison and Match transformations - Survivorship and consolidation rules - Duplicate resolution and golden record creation - Grouping and match strategies |
| Topic 4: Standardization and Cleansing | 20% | - Reference tables and dictionary management - Parser, Standardizer, and Case Converter transformations - Address validation and cleansing |
| Topic 5: Customization and Advanced Features | 8% | - DQ for Excel and other extensions - Custom transformations and rules |
| Topic 6: Data Quality Concepts and Architecture | 15% | - Informatica Data Quality (IDQ) architecture and components - Integration with PowerCenter and Analyst tool - Core data quality principles |
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