PDF VersionHow to Prepare For Data Quality 10 Developer, Professional Certification
Preparation Guide for Data Quality 10 Developer, Professional Certification
Introduction for Data Quality 10 Developer, Professional Certification
This test measures your competency as a member of a project implementation team. This involves an in-depth knowledge of Data Quality processes such as Profiling, Standardization, Matching, and Consolidation. You must select and configure the appropriate Data Quality transformations and build, debug and execute Data Quality mappings including integrating those mappings into Power Center if needed.
The skills and knowledge areas measured by this test are focused on product core functionality inside the realm of a standard project implementation. Training materials, supporting documentation and practical experience may become sources of question development.
This is recommended for students seeking certification as a Data Quality Developer Certified Professional.
The suggested training prerequisites for this certification level are the completion of the following Informatica course(s):
- Data Quality: Advanced Techniques
- Data Quality: Data Quality Management for Developers
- Informatica Analyst
We prepare INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST practice exams and INFORMATICA DATA QUALITY 10 DEVELOPER SPECIALIST practice exams to prepare you for all these requirements.
What is the duration, language, and format of Data Quality 10 Developer, Professional Certification
- Passing grade: 70%
- Number of questions: 70
- Duration of Exam: 90 minutes
- Language of Exam: English, Japanese, Korean
- Type of Questions: Multiple choice (MCQs), multiple answers
- No negative marking for wrong answers
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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)
- Executing mappings in PowerCenter
- Using mappings and mapplets to cleanse and standardize data
- Using Profiles and reference tables to share information with Analysts
- Converting a profile into a mapping
- Performing Address Validation
- Profiling methods to identify data irregularities and inaccuracies
- Identifying duplicate records
- Navigation through the Developer Tool
- Automate and manual consolidation of duplicate records into a master record
- Project Collaboration techniques such as Tags and Comments
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:
- Analytics Professionals
- Business Analysts
- Candidates interested in taking up career under Informatica
- Business Developers
- Mainframe Developers and Architects
- Data Explorers
Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Customization and Advanced Features | 8% | - Custom transformations and rules - DQ for Excel and other extensions |
| Data Profiling | 20% | - Analyzing profile results and quality metrics - Pattern discovery and data domain identification - Column and rule-based profiling |
| Mapping Development and Execution | 12% | - Building and testing IDQ mappings - Parameters, variables, and workflow integration - Debugging and performance tuning |
| Matching and Consolidation | 25% | - Survivorship and consolidation rules - Grouping and match strategies - Comparison and Match transformations - Duplicate resolution and golden record creation |
| Standardization and Cleansing | 20% | - Address validation and cleansing - Parser, Standardizer, and Case Converter transformations - Reference tables and dictionary management |
| Data Quality Concepts and Architecture | 15% | - Core data quality principles - Integration with PowerCenter and Analyst tool - Informatica Data Quality (IDQ) architecture and components |
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