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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:
- Perform and interpret column, rule, comparative and mid-stream profiling
- Apply, configure and troubleshoot data standardization transformations
- Explain Dependency conflict resolution and how it is handled
- Define the difference between the Basic and Advanced Import options available
- Define the techniques for creating mappings for DQ for Excel
- Provide an explanation on how to use the Informatica ribbon in Excel
- Recognize how reference tables are used in the standardization process
- Describe the requirements for integration for Excel
- Be aware of where data standardization fits in the DQ process
- Explain the Web service capabilities required for DQ for Excel
- Describe how to Export a Project
- Differentiate between the various parsing techniques available
How to book the Data Quality 10 Developer, Professional Certification
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- Click Add to Cart and complete your registration/purchase
- Click Enroll and log in to your Informatica account
- Now you can simply Launch and take your test Anytime/Anywhere prior to your test's expiry date
- Once you have registered go to My Training and View Your Transcript
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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:
- Explain what parameters are and why they are used including what parameter functions are supported
- Interpret the AV outputs generated
- Configure Identity Matching option for the match transformation
- Verify the importance of Address Validation
- Describe the process of exporting mappings with parameters built in
- Differentiate between the matching algorithms available and explain how matching scores are
- Explain what Content is, what is contained in the Core Accelerator and why it is used in the Core Accelerator and why it is used
- Develop and build match plans to identify duplicate or related data
- Explain populations, the identity match strategies that are available and how they are used in Identity Matching
- Configure the Address Validation transformation including explaining each mode that is available and what custom templates can be used for
- Identify which Transformations can use parameters
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: Advanced Techniques
- Informatica Analyst
- Data Quality: Data Quality Management for Developers
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Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Mapping Development and Execution | 12% | - Building and testing IDQ mappings - Debugging and performance tuning - Parameters, variables, and workflow integration |
| Topic 2: Matching and Consolidation | 25% | - Survivorship and consolidation rules - Duplicate resolution and golden record creation - Comparison and Match transformations - Grouping and match strategies |
| Topic 3: Customization and Advanced Features | 8% | - Custom transformations and rules - DQ for Excel and other extensions |
| Topic 4: Standardization and Cleansing | 20% | - Address validation and cleansing - Parser, Standardizer, and Case Converter transformations - Reference tables and dictionary management |
| Topic 5: Data Quality Concepts and Architecture | 15% | - Integration with PowerCenter and Analyst tool - Informatica Data Quality (IDQ) architecture and components - Core data quality principles |
| Topic 6: Data Profiling | 20% | - Pattern discovery and data domain identification - Analyzing profile results and quality metrics - Column and rule-based profiling |
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