Your Deduplication Processes May be Leaving You at Risk for GDPR Fines

Once-trusted fuzzy matching algorithms may be leaving your organization vulnerable to hefty GDPR fines. The balancing act of false-positives and false-negatives in single customer view (SCV) systems used to favor the false-negative side, with near negligible error results. However, the standard of that balancing act has now been redefined by the GDPR regulations. Find out how GDPR has moved the…

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Record Matching Made Easy with MatchUp Web Service

MatchUp®, Melissa's solution to identify and eliminate duplicate records, is now available as a web service for batch processes, fulfilling one of most frequent requests from our customers - accurate database matching without maintaining and linking to libraries, or shelling out to the necessary locally-hosted data files. Now you can integrate MatchUp into any aspect of your network that can…

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A 6-Minute MatchUp for SQL Server Tutorial

In this short demo, learn how to eliminate duplicates and merge multiple records into a single, accurate view of your customer - also known as the Golden Record - through a process known as survivorship using Melissa Data's advanced matching tool, MatchUp for SQL Server. Watch our video to learn more!

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Structural Differences and Data Matching

By David Loshin Data matching is easy when the values are exact, but there are different types of variation that complicate matters. Let's start at the foundation: structural differences in the ways that two data sets represent the same concepts. For example, early application systems used data files that were relatively "wide," capturing a lot of information in each record,…

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Modeling Issues and Entity Inheritance

By David Loshin In our last set of posts, we looked at matching and record linkage and how approximate matching could be used to improve the organization's view of "customer centricity." Data quality tools such as parsing, standardization, and business-rule based record linkage and similarity scoring can help in assessing the similarity between two records. The result of the similarity…

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Entities and their Characteristics

By David Loshin How can you tell if two records refer to the same person (or company, or other type of organization)? In our recent posts, we have looked at how data quality techniques such as parsing and standardization help in normalizing the data values within different records so that the records can be compared. But what is being compared?…

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