Read the registration procedure of the Informatica Data Quality 9.x Developer (PR000005) Certification Exam
The registration for the Informatica Data Quality 9.x Developer (PR000005) Exam follows the steps given below.
- Login/register at Webassessor for test taker account
- We recommend that you register for 3 months in advance to get your preferred times and enough time to prepare.
Enough for the tests after 20 or 30 hours'practice
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How can you start preparation for Informatica Data Quality 9.x Developer (PR000005) Certification Exam
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Informatica provides the market-leading data integration platform. There are 500,000 combinations of applications and platforms tested. The data integration platform works with the widest possible range of disparate standards, systems, and applications. This impartial and universal vision makes Informatica unique on the current market as a leader in the data integration platform. So, Informatica becomes the ideal strategic platform for companies wishing to solve data integration problems of any size.
To Pass Data Quality 9.x Developer Specialist Certification, a candidate must pass a written, supervised in-person or webcam exam. The specialized test confirms that the person understands the product and can apply the skills and abilities necessary to contribute to a project as a member of the complete team.
High guarantee for the personal interests of customers
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Informatica PR000005 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Address Validation & Enrichment | 15% | - Configure address validation transformation - Validate and standardize global addresses - Enrich data with reference data |
| Topic 2: Project & Workflow Development | 15% | - Manage dependencies and resolution - Use Informatica Developer tool - Collaborate and deploy projects - Work with parameters and mappings |
| Topic 3: Data Matching & Consolidation | 25% | - Tune match strategies and thresholds - Configure Identity Matching options - Create survivor records and consolidate duplicates - Design and build match plans |
| Topic 4: Data Standardization & Cleansing | 25% | - Implement parsing and normalization rules - Configure standardization transformations - Troubleshoot standardization logic |
| Topic 5: Data Profiling | 20% | - Analyze profiling results and identify anomalies - Understand data quality metrics and patterns - Configure and run data profiling |



