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Understanding functional and technical aspects of Data Quality 10 Developer, Professional Certification
The following will be discussed in INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST exam dumps:
- Remove duplicates using DQA
- Use and describe the functionality of the Analyst Tool including Scorecarding, Reference Table Management, Tags, Filters, Profiles and Comments
- Describe the benefits of project collaboration to a team
- Provide information on the Data Quality process and dimensions of data quality
- Explain Automatic and Manual consolidation techniques and configure the Transformations used for automatic consolidation
- Troubleshoot any problems that may occur
- Generate a survivor record in the DQA
- Use the Exception Transformation to generate and populate the Bad Records and Duplicate Records tables
- Explain how to integrate IDQ mappings and mapplets into PowerCenter Workflows including how content is handled
- Describe the Informatica 10 architecture and set up including the repositories required for installation
- Describe how Analysts and Developers can collaborate on projects
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What is the duration, language, and format of Data Quality 10 Developer, Professional Certification
- Language of Exam: English, Japanese, Korean
- No negative marking for wrong answers
- Duration of Exam: 90 minutes
- Number of questions: 70
- Passing grade: 70%
- Type of Questions: Multiple choice (MCQs), multiple answers
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Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Profiling | 20% | - Pattern discovery and data domain identification - Column and rule-based profiling - Analyzing profile results and quality metrics |
| Topic 2: Matching and Consolidation | 25% | - Survivorship and consolidation rules - Comparison and Match transformations - Duplicate resolution and golden record creation - Grouping and match strategies |
| Topic 3: Customization and Advanced Features | 8% | - Custom transformations and rules - DQ for Excel and other extensions |
| Topic 4: Mapping Development and Execution | 12% | - Building and testing IDQ mappings - Parameters, variables, and workflow integration - Debugging and performance tuning |
| Topic 5: Data Quality Concepts and Architecture | 15% | - Core data quality principles - Integration with PowerCenter and Analyst tool - Informatica Data Quality (IDQ) architecture and components |
| Topic 6: Standardization and Cleansing | 20% | - Reference tables and dictionary management - Address validation and cleansing - Parser, Standardizer, and Case Converter transformations |
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