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How much Data Quality 10 Developer, Professional Certification Cost

The cost of the Data Quality 10 Developer, Professional Certification is $200. For more information related to exam price, please visit the official website Google Website as the cost of exams may be subjected to vary county-wise.

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):

  • Informatica Analyst
  • Data Quality: Advanced Techniques
  • Data Quality: Data Quality Management for Developers

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:

  • Verify the importance of Address Validation
  • Configure Identity Matching option for the match transformation
  • 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
  • Explain what parameters are and why they are used including what parameter functions are supported
  • Differentiate between the matching algorithms available and explain how matching scores are
  • Identify which Transformations can use parameters
  • Interpret the AV outputs generated
  • Describe the process of exporting mappings with parameters built in
  • 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

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:

  • Provide information on the Data Quality process and dimensions of data quality
  • Use the Exception Transformation to generate and populate the Bad Records and Duplicate Records tables
  • Use and describe the functionality of the Analyst Tool including Scorecarding, Reference Table Management, Tags, Filters, Profiles and Comments
  • Explain how to integrate IDQ mappings and mapplets into PowerCenter Workflows including how content is handled
  • Generate a survivor record in the DQA
  • Remove duplicates using DQA
  • Describe how Analysts and Developers can collaborate on projects
  • Describe the benefits of project collaboration to a team
  • Troubleshoot any problems that may occur
  • Describe the Informatica 10 architecture and set up including the repositories required for installation
  • Explain Automatic and Manual consolidation techniques and configure the Transformations used for automatic consolidation

Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:

SectionWeightObjectives
Customization and Advanced Features8%- DQ for Excel and other extensions
- Custom transformations and rules
Matching and Consolidation25%- Comparison and Match transformations
- Grouping and match strategies
- Duplicate resolution and golden record creation
- Survivorship and consolidation rules
Data Quality Concepts and Architecture15%- Informatica Data Quality (IDQ) architecture and components
- Core data quality principles
- Integration with PowerCenter and Analyst tool
Data Profiling20%- Column and rule-based profiling
- Analyzing profile results and quality metrics
- Pattern discovery and data domain identification
Mapping Development and Execution12%- Parameters, variables, and workflow integration
- Building and testing IDQ mappings
- Debugging and performance tuning
Standardization and Cleansing20%- Reference tables and dictionary management
- Parser, Standardizer, and Case Converter transformations
- Address validation and cleansing
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