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The benefit of obtaining the Data Quality 10 Developer, Professional Certification Certification
- Reduce costs for the business
- Reduce risks by identifying, resolving, and preventing costly data problems
- Achieve better business outcomes and maximize the return on data
- Enhance IT productivity and business self-sufficiency with powerful business-IT collaboration tools
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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:
- Differentiate between the various parsing techniques available
- Explain the Web service capabilities required for DQ for Excel
- Recognize how reference tables are used in the standardization process
- Define the techniques for creating mappings for DQ for Excel
- Define the difference between the Basic and Advanced Import options available
- Describe how to Export a Project
- Describe the requirements for integration for Excel
- Be aware of where data standardization fits in the DQ process
- Explain Dependency conflict resolution and how it is handled
- Perform and interpret column, rule, comparative and mid-stream profiling
- Apply, configure and troubleshoot data standardization transformations
- Provide an explanation on how to use the Informatica ribbon in Excel
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Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Data Quality Concepts and Architecture | 15% | - Core data quality principles - Informatica Data Quality (IDQ) architecture and components - Integration with PowerCenter and Analyst tool |
| Topic 2: Standardization and Cleansing | 20% | - Reference tables and dictionary management - Parser, Standardizer, and Case Converter transformations - Address validation and cleansing |
| Topic 3: Matching and Consolidation | 25% | - Comparison and Match transformations - Grouping and match strategies - Survivorship and consolidation rules - Duplicate resolution and golden record creation |
| Topic 4: Data Profiling | 20% | - Analyzing profile results and quality metrics - Pattern discovery and data domain identification - Column and rule-based profiling |
| Topic 5: Mapping Development and Execution | 12% | - Parameters, variables, and workflow integration - Debugging and performance tuning - Building and testing IDQ mappings |
| Topic 6: Customization and Advanced Features | 8% | - Custom transformations and rules - DQ for Excel and other extensions |
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