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:
- Describe the benefits of project collaboration to a team
- Explain how to integrate IDQ mappings and mapplets into PowerCenter Workflows including how content is handled
- Explain Automatic and Manual consolidation techniques and configure the Transformations used for automatic consolidation
- Use the Exception Transformation to generate and populate the Bad Records and Duplicate Records tables
- Provide information on the Data Quality process and dimensions of data quality
- Remove duplicates using DQA
- Generate a survivor record in the DQA
- Describe the Informatica 10 architecture and set up including the repositories required for installation
- Describe how Analysts and Developers can collaborate on projects
- Troubleshoot any problems that may occur
- Use and describe the functionality of the Analyst Tool including Scorecarding, Reference Table Management, Tags, Filters, Profiles and Comments
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What is the duration, language, and format of Data Quality 10 Developer, Professional Certification
- Type of Questions: Multiple choice (MCQs), multiple answers
- No negative marking for wrong answers
- Duration of Exam: 90 minutes
- Number of questions: 70
- Language of Exam: English, Japanese, Korean
- Passing grade: 70%
Very high passing rate
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Topics of Data Quality 10 Developer, Professional Certification
INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST exam dumps pdf will include the following topics:
- Object Import and Export
- Matching
- Integration with PowerCenter
- Address Validation
- Content
- Analyst Collaboration
- Parameters
- Standardization/Mapplets
- Consolidation and the DQA
- Informatica Overview
- Profiling
- DQ for Excel
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:
- Differentiate between the matching algorithms available and explain how matching scores are
- Explain what parameters are and why they are used including what parameter functions are supported
- 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
- Explain populations, the identity match strategies that are available and how they are used in Identity Matching
- Describe the process of exporting mappings with parameters built in
- Configure Identity Matching option for the match transformation
- Develop and build match plans to identify duplicate or related data
- Configure the Address Validation transformation including explaining each mode that is available and what custom templates can be used for
- Identify which Transformations can use parameters
- Interpret the AV outputs generated
- Verify the importance of Address Validation
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Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
| Integration with PowerCenter | 5% | - Execution and Deployment
- 1. Integration workflows
- 2. Running mappings in PowerCenter
|
| Address Validation | 5% | - Address Validation Transformation
- 1. Output interpretation
- 2. Validation modes and configuration
|
| Matching | 10% | - Match Logic
- 1. Match rules and strategies
- 2. Identity matching concepts
|
| Standardization and Mapplets | 10% | - Data Standardization
- 1. Standardizer transformation usage
- 2. Reference tables in standardization
- 3. Parsing techniques
|
| Informatica Platform Overview | 10% | - Architecture and Components
- 1. Repository and services setup
- 2. Informatica Data Quality architecture concepts
|
| Object Import and Export | 5% | - Metadata Management
- 1. Import/export of mappings and objects
|
| Consolidation and Data Quality Applications (DQA) | 10% | - Data Consolidation
- 1. Master record creation
- 2. Duplicate record handling
|
| Data Profiling | 15% | - Profiling Methods
- 1. Column profiling
- 2. Rule-based profiling
- 3. Comparative profiling
|
| DQ for Excel | 5% | - Excel-based Data Quality
- 1. Web service integration with Excel
|
| Parameters | 5% | - Runtime Configuration
- 1. Parameter files and runtime variables
|
| Content | 10% | - Prebuilt Content Usage
- 1. Accelerators and reference data
|
| Analyst Collaboration | 10% | - Analyst Tool Usage
- 1. Scorecards, profiling, filters, tags
- 2. Collaboration between Analyst and Developer
|