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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)
Navigation through the Developer Tool
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
Identifying duplicate records
Performing Address Validation
Automate and manual consolidation of duplicate records into a master record
Profiling methods to identify data irregularities and inaccuracies
Project Collaboration techniques such as Tags and Comments
Executing mappings in PowerCenter

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:

Candidates interested in taking up career under Informatica
Data Explorers
Mainframe Developers and Architects
Business Developers
Analytics Professionals
Business Analysts

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How 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.

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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 GuideTorrent exam dumps to increase retention and improve preparation.

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Informatica Data-Quality-10-Developer-Specialist Exam Syllabus Topics:

Section	Weight	Objectives
Data Profiling	15%	- Profiling Methods 1. Comparative profiling 2. Column profiling 3. Rule-based profiling
Content	10%	- Prebuilt Content Usage 1. Accelerators and reference data
Standardization and Mapplets	10%	- Data Standardization 1. Reference tables in standardization 2. Standardizer transformation usage 3. Parsing techniques
Address Validation	5%	- Address Validation Transformation 1. Validation modes and configuration 2. Output interpretation
Consolidation and Data Quality Applications (DQA)	10%	- Data Consolidation 1. Duplicate record handling 2. Master record creation
Object Import and Export	5%	- Metadata Management 1. Import/export of mappings and objects
Parameters	5%	- Runtime Configuration 1. Parameter files and runtime variables
Informatica Platform Overview	10%	- Architecture and Components 1. Informatica Data Quality architecture concepts 2. Repository and services setup
Matching	10%	- Match Logic 1. Match rules and strategies 2. Identity matching concepts
Analyst Collaboration	10%	- Analyst Tool Usage 1. Collaboration between Analyst and Developer 2. Scorecards, profiling, filters, tags
Integration with PowerCenter	5%	- Execution and Deployment 1. Integration workflows 2. Running mappings in PowerCenter
DQ for Excel	5%	- Excel-based Data Quality 1. Web service integration with Excel