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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:
- Standardization/Mapplets
- Analyst Collaboration
- Consolidation and the DQA
- Profiling
- Matching
- Address Validation
- Integration with PowerCenter
- Informatica Overview
- Parameters
- Content
- Object Import and Export
- DQ for Excel
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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 requirements for integration for Excel
- Explain the Web service capabilities required for DQ for Excel
- Describe how to Export a Project
- Define the difference between the Basic and Advanced Import options available
- Apply, configure and troubleshoot data standardization transformations
- Recognize how reference tables are used in the standardization process
- Perform and interpret column, rule, comparative and mid-stream profiling
- Differentiate between the various parsing techniques available
- Be aware of where data standardization fits in the DQ process
- Provide an explanation on how to use the Informatica ribbon in Excel
- Define the techniques for creating mappings for DQ for Excel
- Explain Dependency conflict resolution and how it is handled
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With the increased digitization of the economy, a humongous amount of semi-structured and unstructured data is emanating from various sources. Due to this unmatched format of data, the need for data integration to process the data becomes a necessity. Informatica is widely known for its data integration abilities across the globe.
Informatica PowerCenter allows migrating, integrating, and governing the enterprise-wide data, and hence it has attracted many aspirants to build careers in this lucrative domain. Merely getting the training does not lead people to success; a certification has become the need of the hour. Before taking up this test, an applicant must make sure that he/she has the skills in Informatica architecture, service maintenance, security, deployment, license keys, repository management, web services, command-line interfaces, metadata reporting, and administrator tool. You can use DumpsQuestion exam dumps to increase retention and improve preparation.
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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)
- Converting a profile into a mapping
- Profiling methods to identify data irregularities and inaccuracies
- Navigation through the Developer Tool
- Automate and manual consolidation of duplicate records into a master record
- Identifying duplicate records
- Project Collaboration techniques such as Tags and Comments
- Executing mappings in PowerCenter
- Performing Address Validation
- Using mappings and mapplets to cleanse and standardize data
- 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:
- Analytics Professionals
- Business Analysts
- Data Explorers
- Mainframe Developers and Architects
- Business Developers
- Candidates interested in taking up career under Informatica
Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Quality Concepts and Architecture | 15% | - Integration with PowerCenter and Analyst tool - Informatica Data Quality (IDQ) architecture and components - Core data quality principles |
| Customization and Advanced Features | 8% | - Custom transformations and rules - DQ for Excel and other extensions |
| Standardization and Cleansing | 20% | - Parser, Standardizer, and Case Converter transformations - Address validation and cleansing - Reference tables and dictionary management |
| Matching and Consolidation | 25% | - Grouping and match strategies - Comparison and Match transformations - Duplicate resolution and golden record creation - Survivorship and consolidation rules |
| Data Profiling | 20% | - Column and rule-based profiling - Analyzing profile results and quality metrics - Pattern discovery and data domain identification |
| Mapping Development and Execution | 12% | - Debugging and performance tuning - Building and testing IDQ mappings - Parameters, variables, and workflow integration |




