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Who should take the Data Quality 10 Developer, Professional Certification

People who are familiar with:

  • Using Profiles and reference tables to share information with Analysts
  • Executing mappings in PowerCenter
  • Converting a profile into a mapping
  • Profiling methods to identify data irregularities and inaccuracies
  • Using mappings and mapplets to cleanse and standardize data
  • Performing Address Validation
  • Automate and manual consolidation of duplicate records into a master record
  • Deploying Data Quality Mappings in an Excel spreadsheet (connect to Web Services)
  • Project Collaboration techniques such as Tags and Comments
  • Identifying duplicate records
  • Navigation through the Developer Tool

Peoplw who want to learn how to run data quality mapping on Excel spread sheets in this module (Power Center Integration, Performing Consolidation, grouping data and DQ Matching Cluster Analysis, GUI, Mappings Mapplets and Reusable AV Transformation.etc) and identify, resolve, and prevent costly data problems can consult INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST practice exam and INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST practice exams.

With a number of opportunities in the field, the following job roles will get benefited from this exam:

  • Business Developers
  • Analytics Professionals
  • Data Explorers
  • Candidates interested in taking up career under Informatica
  • Mainframe Developers and Architects
  • Business Analysts

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

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

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