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:
- Troubleshoot any problems that may occur
- Describe the Informatica 10 architecture and set up including the repositories required for installation
- Explain how to integrate IDQ mappings and mapplets into PowerCenter Workflows including how content is handled
- Generate a survivor record in the 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
- Remove duplicates using DQA
- Provide information on the Data Quality process and dimensions of data quality
- Describe how Analysts and Developers can collaborate on projects
- Explain Automatic and Manual consolidation techniques and configure the Transformations used for automatic consolidation
- Use the Exception Transformation to generate and populate the Bad Records and Duplicate Records tables
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- Define the techniques for creating mappings for DQ for Excel
- Explain the Web service capabilities required 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
- Be aware of where data standardization fits in the DQ process
- Describe how to Export a Project
- Explain Dependency conflict resolution and how it is handled
- Apply, configure and troubleshoot data standardization transformations
- Recognize how reference tables are used in the standardization process
- Perform and interpret column, rule, comparative and mid-stream profiling
- Describe the requirements for integration for Excel
- Differentiate between the various parsing techniques available
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How to Prepare For Data Quality 10 Developer, Professional Certification
Preparation Guide for Data Quality 10 Developer, Professional Certification
Introduction for Data Quality 10 Developer, Professional Certification
This test measures your competency as a member of a project implementation team. This involves an in-depth knowledge of Data Quality processes such as Profiling, Standardization, Matching, and Consolidation. You must select and configure the appropriate Data Quality transformations and build, debug and execute Data Quality mappings including integrating those mappings into Power Center if needed.
The skills and knowledge areas measured by this test are focused on product core functionality inside the realm of a standard project implementation. Training materials, supporting documentation and practical experience may become sources of question development.
This is recommended for students seeking certification as a Data Quality Developer Certified Professional.
The suggested training prerequisites for this certification level are the completion of the following Informatica course(s):
- Data Quality: Data Quality Management for Developers
- Informatica Analyst
- Data Quality: Advanced Techniques
We prepare INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST practice exams and INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST practice exams to prepare you for all these requirements.
Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Matching and Consolidation | 25% | - Grouping and match strategies - Duplicate resolution and golden record creation - Comparison and Match transformations - Survivorship and consolidation rules |
| Data Quality Concepts and Architecture | 15% | - Informatica Data Quality (IDQ) architecture and components - Integration with PowerCenter and Analyst tool - Core data quality principles |
| Data Profiling | 20% | - Analyzing profile results and quality metrics - Pattern discovery and data domain identification - Column and rule-based profiling |
| Customization and Advanced Features | 8% | - DQ for Excel and other extensions - Custom transformations and rules |
| Standardization and Cleansing | 20% | - Reference tables and dictionary management - Address validation and cleansing - Parser, Standardizer, and Case Converter transformations |
| Mapping Development and Execution | 12% | - Debugging and performance tuning - Building and testing IDQ mappings - Parameters, variables, and workflow integration |



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