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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Inferred Knowledge and Customer Intelligence through Matching and Linkage

By David Loshin What I have found to be the most interesting byproduct of record linkage is the ability to infer explicit facts about individuals that are obfuscated as a result of distribution of data. As an example, consider these records, taken from different data sets: A: David Loshin 301-754-6350 1163 Kersey Rd Silver Spring MD 20902 B: Knowledge Integrity,…

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Are You A Dupe Detective?

By Joseph Vertido The process of finding approximate matching records in your data to get rid of duplicates is precisely that - fuzzy. It raises as many questions as answers. Am I using a good matching algorithm? Am I matching on the right fields? Is it a true match or a false one? The problem begins when inconsistent data enters…

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