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Data parsing, standardization, matching, and de-duplication are the cornerstones of successful Master Data Management (MDM). They are also critical parts of successful data quality programs, and are key steps in building data warehouses as well as any data integration and consolidation initiatives. You could say that today few organizations can function effectively without implementing data parsing and matching processes often in many data domains.
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This need is further magnified if your company has gone global and plans to create databases that combine name- and address-related data from all corners of the world. Managing global information effectively takes specialist knowledge and the ability to show consideration for the differences that exist throughout the world. Worldwide there are more than 10,000 languages, 130 address formats, 36 personal and hundreds of business name formats. All of these variables are further complicated by the need to respect national and regional cultures. Failure to consider formats, styles, and cultures has huge impact on quality of data and quality of business relationships.
This online training course is aimed at data quality and master data management (MDM) professionals as well as those responsible to work with global information. The field is broad and the details are many. The purpose of this course is to provide a broad and in-depth review of data parsing, standardization, matching, and de-duplication techniques, as well as extensive overview of specific problems and solutions when dealing with global data.
You will learn:
- Data parsing, standardization, matching, and de-duplication techniques
- How to find and use external reference data
- How data parsing and matching contribute to improving data quality, MDM, and data warehousing
- Which data domains, entities and data elements may benefit from data parsing and matching
- Challenges of global data and ways to overcome these challenges
This course is geared towards:
- master data management professionals
- data quality professionals
- information architects
- developers of data warehousing systems
- business professionals who work with global data
Module 0. About the Course (12 min)
Module 1. Introduction (17 min)
Module 2. Implementation Fundamentals (70 min)
- Parsing and Standardization
- Introduction to Data Matching
- Data Matching Techniques
- Data Matching Destinations
- Evaluating Data Matching Tools
Module 3. External Reference Data (45 min)
- External Data Sources
- Syndicated Customer Data
- Syndicated Product Data
- Using the Web
Module 4. Challenges of Global Data (58 min)
- Introduction to Global Information
- Global Data: What You Need to Know
- Variations by Country and Region
- Cultural Impacts
- Characters and Diacritics
Module 5. Overcoming the Challenges of Global Data (59 min)
- Data Profiling
- Consistent Data Structures
- Preparing Global Data for Effective Use
Click –here- to download a more detailed outline of this course.
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This exam tests knowledge and understanding of basic concepts and principles of data parsing, matching, and deduplication.
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You will be tested in these areas:
- Principles and techniques of data parsing, standardization, matching, and deduplication
- Finding and using external reference data
- The domains, entities, and data elements that benefit from data parsing and matching
- The challenges of global data
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Additional Information
Number of Questions: 25
Time Limit: 50 Minutes
Passing Score: 70%
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Once you pass the exam, you will receive a Certificate of Education
documenting that you have demonstrated mastery of the topic. Course
exams count towards eLC certification programs. Visit our Certification page for more information about our various programs.
We recommend that you take detailed notes and review the course material multiple times before taking this exam. Click here to learn more about CIMP exams.
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Course Review 
Course Review