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Data Quality 10 Developer, Professional Certification Path
This is a fundamental exam and gives credential of Data Quality Developer Certified Professional.
What is the duration, language, and format of Data Quality 10 Developer, Professional Certification
- Language of Exam: English, Japanese, Korean
- Number of questions: 70
- Type of Questions: Multiple choice (MCQs), multiple answers
- Passing grade: 70%
- Duration of Exam: 90 minutes
- No negative marking for wrong answers
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The following will be discussed in INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST exam dumps:
- Explain the Web service capabilities required for DQ for Excel
- Apply, configure and troubleshoot data standardization transformations
- Describe how to Export a Project
- Be aware of where data standardization fits in the DQ process
- Define the techniques for creating mappings for DQ for Excel
- Provide an explanation on how to use the Informatica ribbon in Excel
- Define the difference between the Basic and Advanced Import options available
- Perform and interpret column, rule, comparative and mid-stream profiling
- Recognize how reference tables are used in the standardization process
- Differentiate between the various parsing techniques available
- Describe the requirements for integration for Excel
- Explain Dependency conflict resolution and how it is handled
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Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Customization and Advanced Features | 8% | - Custom transformations and rules - DQ for Excel and other extensions |
| Data Quality Concepts and Architecture | 15% | - Integration with PowerCenter and Analyst tool - Informatica Data Quality (IDQ) architecture and components - Core data quality principles |
| Data Profiling | 20% | - Analyzing profile results and quality metrics - Pattern discovery and data domain identification - Column and rule-based profiling |
| Mapping Development and Execution | 12% | - Parameters, variables, and workflow integration - Building and testing IDQ mappings - Debugging and performance tuning |
| Matching and Consolidation | 25% | - Grouping and match strategies - Duplicate resolution and golden record creation - Comparison and Match transformations - Survivorship and consolidation rules |
| Standardization and Cleansing | 20% | - Parser, Standardizer, and Case Converter transformations - Address validation and cleansing - Reference tables and dictionary management |




