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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.
Who should take the Data Quality 10 Developer, Professional Certification
People who are familiar with:
- Deploying Data Quality Mappings in an Excel spreadsheet (connect to Web Services)
- Performing Address Validation
- Executing mappings in PowerCenter
- Profiling methods to identify data irregularities and inaccuracies
- Using mappings and mapplets to cleanse and standardize data
- Identifying duplicate records
- Automate and manual consolidation of duplicate records into a master record
- Project Collaboration techniques such as Tags and Comments
- Converting a profile into a mapping
- Navigation through the Developer Tool
- Using Profiles and reference tables to share information with Analysts
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:
- Mainframe Developers and Architects
- Business Developers
- Data Explorers
- Analytics Professionals
- Candidates interested in taking up career under Informatica
- Business Analysts
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Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Profiling | 20% | - Column and rule-based profiling - Analyzing profile results and quality metrics - Pattern discovery and data domain identification |
| Matching and Consolidation | 25% | - Duplicate resolution and golden record creation - Grouping and match strategies - Survivorship and consolidation rules - Comparison and Match transformations |
| Data Quality Concepts and Architecture | 15% | - Integration with PowerCenter and Analyst tool - Informatica Data Quality (IDQ) architecture and components - Core data quality principles |
| Standardization and Cleansing | 20% | - Parser, Standardizer, and Case Converter transformations - Reference tables and dictionary management - Address validation and cleansing |
| Mapping Development and Execution | 12% | - Parameters, variables, and workflow integration - Debugging and performance tuning - Building and testing IDQ mappings |
| Customization and Advanced Features | 8% | - DQ for Excel and other extensions - Custom transformations and rules |
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