Informatica Data-Quality-10-Developer-Specialist exam dumps : Data Quality 10: Developer Specialist Exam

  • Exam Code: Data-Quality-10-Developer-Specialist
  • Exam Name: Data Quality 10: Developer Specialist Exam
  • Updated: Sep 07, 2026     Q & A: 70 Questions and Answers

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

What is the duration, language, and format of Data Quality 10 Developer, Professional Certification

  • Language of Exam: English, Japanese, Korean
  • No negative marking for wrong answers
  • Passing grade: 70%
  • Duration of Exam: 90 minutes
  • Type of Questions: Multiple choice (MCQs), multiple answers
  • Number of questions: 70

The Data Quality 10: Developer Specialist Exam certification exam is ideal for professionals who are responsible for data quality management, data integration, and data governance in their organizations. It is also suitable for developers, consultants, and technical architects who work with the IDQ tool and are involved in the development and deployment of data quality solutions for their clients. Data-Quality-10-Developer-Specialist exam is a great opportunity for professionals to demonstrate their skills and knowledge in the field of data quality development and set themselves apart from their peers.

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Informatica Data-Quality-10-Developer-Specialist, also known as the Data Quality 10: Developer Specialist, is a certification exam designed for professionals who specialize in data quality development using the Informatica Data Quality (IDQ) tool. The IDQ tool is a powerful data quality management system that allows users to cleanse, standardize, and validate data from various sources, ensuring that the data is accurate, complete, and consistent.

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To obtain the certification, candidates must pass a rigorous exam that consists of multiple-choice questions and scenario-based questions. Data-Quality-10-Developer-Specialist exam is conducted online and can be taken from anywhere in the world. The duration of the exam is two hours, and candidates must score at least 70% to pass.

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

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

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