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Data Parsing, Matching and De-duplication
Data Parsing, Matching and De-duplication - online training course
 
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4-hour 20-min Online Course
by Kathy Hunter, William McKnight, Henrik Sørensen
Single-user access license
Our Price: $435.00


Product Code: MDM-02-A


Course Exam [Add $100.00]

Description Course Outline Exam Details
 

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

Average Customer Review: Average Customer Review: 4 of 5 4 of 5 Total Reviews: 20 Write a review.

  0 of 0 people found the following review helpful:
 
4 of 5 Course Review August 10, 2023
Reviewer: Lokesh Pandey  
Very good presentation, flow was very good. Matches with the real problem which we face globally. I would prefer to have some practicals, as they always helps!

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  0 of 0 people found the following review helpful:
 
4 of 5 Course Review May 21, 2020
Reviewer: Liang Hung Ng  
Nice to have multiple lecturers in one module. However, there's some degree of duplication in course content. It will also be nice if there is an option to speed up the playback.

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  0 of 0 people found the following review helpful:
 
5 of 5 Course Review January 13, 2020
Reviewer: Jeremiah Tamagna-Derr  
While the course did provide a lot of material on parsing, matching, de-duplication there were large segments about syndicated and global data that were not anticipated.  Coming on the heels of the previous MDM module some of this material seemed redundant.

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  0 of 0 people found the following review helpful:
 
4 of 5 Course Review July 18, 2019
Reviewer: Mi Son Major  
I liked examples.  If you could have more examples for each topic, I think visually, it will sink in more to the students.  Example: diacritics, okay, you gave me an audio definition but what does it look like on the data.

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  0 of 0 people found the following review helpful:
 
4 of 5 Course Review December 19, 2016
Reviewer: Jonathan Schoonover  
Only changes I would recomend are a few practicle exercises.

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