Informatica Data-Quality-10-Developer-Specialist Exam : Data Quality 10: Developer Specialist Exam

Informatica Data-Quality-10-Developer-Specialist exam
  • Exam Code: Data-Quality-10-Developer-Specialist
  • Exam Name: Data Quality 10: Developer Specialist Exam
  • Updated: Jul 25, 2026
  • Q & A: 70 Questions and Answers
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The following will be discussed in INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST exam dumps:

  • Provide an explanation on how to use the Informatica ribbon in Excel
  • Explain Dependency conflict resolution and how it is handled
  • Differentiate between the various parsing techniques available
  • Recognize how reference tables are used in the standardization process
  • Explain the Web service capabilities required for DQ for Excel
  • Apply, configure and troubleshoot data standardization transformations
  • Describe the requirements for integration for Excel
  • Perform and interpret column, rule, comparative and mid-stream profiling
  • Define the techniques for creating mappings for DQ for Excel
  • Describe how to Export a Project
  • Be aware of where data standardization fits in the DQ process
  • Define the difference between the Basic and Advanced Import options available
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Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
SectionWeightObjectives
Topic 1: Mapping Development and Execution12%- Debugging and performance tuning
- Building and testing IDQ mappings
- Parameters, variables, and workflow integration
Topic 2: Customization and Advanced Features8%- DQ for Excel and other extensions
- Custom transformations and rules
Topic 3: Data Profiling20%- Analyzing profile results and quality metrics
- Column and rule-based profiling
- Pattern discovery and data domain identification
Topic 4: Standardization and Cleansing20%- Reference tables and dictionary management
- Address validation and cleansing
- Parser, Standardizer, and Case Converter transformations
Topic 5: Data Quality Concepts and Architecture15%- Integration with PowerCenter and Analyst tool
- Core data quality principles
- Informatica Data Quality (IDQ) architecture and components
Topic 6: Matching and Consolidation25%- Duplicate resolution and golden record creation
- Grouping and match strategies
- Comparison and Match transformations
- Survivorship and consolidation rules

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