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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.
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Topics of Data Quality 10 Developer, Professional Certification
INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST exam dumps pdf will include the following topics:
- Integration with PowerCenter
- DQ for Excel
- Standardization/Mapplets
- Analyst Collaboration
- Parameters
- Consolidation and the DQA
- Object Import and Export
- Address Validation
- Content
- Informatica Overview
- Profiling
- Matching
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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:
- Describe how to Export a Project
- Differentiate between the various parsing techniques available
- Explain Dependency conflict resolution and how it is handled
- Describe the requirements for integration for Excel
- Provide an explanation on how to use the Informatica ribbon in Excel
- Define the techniques for creating mappings for DQ for Excel
- Apply, configure and troubleshoot data standardization transformations
- Define the difference between the Basic and Advanced Import options available
- Recognize how reference tables are used in the standardization process
- Explain the Web service capabilities required for DQ for Excel
- Be aware of where data standardization fits in the DQ process
- Perform and interpret column, rule, comparative and mid-stream profiling
Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Address Validation | 5% | - Address Validation Transformation
|
| DQ for Excel | 5% | - Excel-based Data Quality
|
| Integration with PowerCenter | 5% | - Execution and Deployment
|
| Informatica Platform Overview | 10% | - Architecture and Components
|
| Consolidation and Data Quality Applications (DQA) | 10% | - Data Consolidation
|
| Parameters | 5% | - Runtime Configuration
|
| Data Profiling | 15% | - Profiling Methods
|
| Matching | 10% | - Match Logic
|
| Object Import and Export | 5% | - Metadata Management
|
| Standardization and Mapplets | 10% | - Data Standardization
|
| Content | 10% | - Prebuilt Content Usage
|
| Analyst Collaboration | 10% | - Analyst Tool Usage
|







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