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