Informatica Data-Quality-10-Developer-Specialist real exam prep : Data Quality 10: Developer Specialist Exam

  • Exam Code: Data-Quality-10-Developer-Specialist
  • Exam Name: Data Quality 10: Developer Specialist Exam
  • Updated: Aug 13, 2026
  • Q&As: 70 Questions and Answers

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About Informatica Data-Quality-10-Developer-Specialist Real Exam

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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With the increased digitization of the economy, a humongous amount of semi-structured and unstructured data is emanating from various sources. Due to this unmatched format of data, the need for data integration to process the data becomes a necessity. Informatica is widely known for its data integration abilities across the globe.

Informatica PowerCenter allows migrating, integrating, and governing the enterprise-wide data, and hence it has attracted many aspirants to build careers in this lucrative domain. Merely getting the training does not lead people to success; a certification has become the need of the hour. Before taking up this test, an applicant must make sure that he/she has the skills in Informatica architecture, service maintenance, security, deployment, license keys, repository management, web services, command-line interfaces, metadata reporting, and administrator tool. You can use TestkingPass exam dumps to increase retention and improve preparation.

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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:

  • Be aware of where data standardization fits in the DQ process
  • Define the techniques for creating mappings for DQ for Excel
  • Explain the Web service capabilities required for DQ for Excel
  • Explain Dependency conflict resolution and how it is handled
  • Define the difference between the Basic and Advanced Import options available
  • Differentiate between the various parsing techniques available
  • Provide an explanation on how to use the Informatica ribbon in Excel
  • Describe how to Export a Project
  • Perform and interpret column, rule, comparative and mid-stream profiling
  • Describe the requirements for integration for Excel
  • Recognize how reference tables are used in the standardization process
  • Apply, configure and troubleshoot data standardization transformations

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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:

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

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

SectionWeightObjectives
Topic 1: Integration with PowerCenter5%- Execution and Deployment
  • 1. Integration workflows
    • 2. Running mappings in PowerCenter
      Topic 2: Address Validation5%- Address Validation Transformation
      • 1. Validation modes and configuration
        • 2. Output interpretation
          Topic 3: Parameters5%- Runtime Configuration
          • 1. Parameter files and runtime variables
            Topic 4: DQ for Excel5%- Excel-based Data Quality
            • 1. Web service integration with Excel
              Topic 5: Informatica Platform Overview10%- Architecture and Components
              • 1. Informatica Data Quality architecture concepts
                • 2. Repository and services setup
                  Topic 6: Data Profiling15%- Profiling Methods
                  • 1. Comparative profiling
                    • 2. Column profiling
                      • 3. Rule-based profiling
                        Topic 7: Analyst Collaboration10%- Analyst Tool Usage
                        • 1. Scorecards, profiling, filters, tags
                          • 2. Collaboration between Analyst and Developer
                            Topic 8: Standardization and Mapplets10%- Data Standardization
                            • 1. Parsing techniques
                              • 2. Standardizer transformation usage
                                • 3. Reference tables in standardization
                                  Topic 9: Consolidation and Data Quality Applications (DQA)10%- Data Consolidation
                                  • 1. Duplicate record handling
                                    • 2. Master record creation
                                      Topic 10: Content10%- Prebuilt Content Usage
                                      • 1. Accelerators and reference data
                                        Topic 11: Object Import and Export5%- Metadata Management
                                        • 1. Import/export of mappings and objects
                                          Topic 12: Matching10%- Match Logic
                                          • 1. Identity matching concepts
                                            • 2. Match rules and strategies

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