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The following will be discussed in INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST exam dumps:
- Explain what parameters are and why they are used including what parameter functions are supported
- Differentiate between the matching algorithms available and explain how matching scores are
- Verify the importance of Address Validation
- Describe the process of exporting mappings with parameters built in
- Develop and build match plans to identify duplicate or related data
- Configure the Address Validation transformation including explaining each mode that is available and what custom templates can be used for
- Configure Identity Matching option for the match transformation
- Explain what Content is, what is contained in the Core Accelerator and why it is used in the Core Accelerator and why it is used
- Explain populations, the identity match strategies that are available and how they are used in Identity Matching
- Interpret the AV outputs generated
- Identify which Transformations can use parameters
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Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Mapping Development and Execution | 12% | - Building and testing IDQ mappings - Debugging and performance tuning - Parameters, variables, and workflow integration |
| Data Profiling | 20% | - Analyzing profile results and quality metrics - Pattern discovery and data domain identification - Column and rule-based profiling |
| Customization and Advanced Features | 8% | - Custom transformations and rules - DQ for Excel and other extensions |
| Data Quality Concepts and Architecture | 15% | - Informatica Data Quality (IDQ) architecture and components - Integration with PowerCenter and Analyst tool - Core data quality principles |
| Matching and Consolidation | 25% | - Survivorship and consolidation rules - Duplicate resolution and golden record creation - Comparison and Match transformations - Grouping and match strategies |
| Standardization and Cleansing | 20% | - Parser, Standardizer, and Case Converter transformations - Address validation and cleansing - Reference tables and dictionary management |






