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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Tips & Tricks for Global MatchUp Matching Strategies

by Tim Sidor, Data Quality Analyst In the past we've discussed implementing different matching strategies based on how you would like your records grouped. For example. By "Address"? or by "Name and Address". The former would match 'John' and 'Mary Smith' at the same household, whereas the latter would identify them as unique entities. For Global processing, even after determining…

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How to Do It All with Melissa

With Melissa, you can do it all - see for yourself with the brand new Solutions Catalog. This catalog showcases products to transform your people data (names, addresses, emails, phone numbers) into accurate, actionable insight. Our products are in the Cloud or available via easy plugins and APIs. We provide solutions to power Know Your Customer initiatives, improve mail deliverability…

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MatchUp Now Available in the Cloud

Did you know that most databases contain 8-10% duplicates? These duplicates get in the way of business intelligence, accurate analytics, and can even result in wasted spend and undeliverable mail costs.   The solution? MatchUp®! The new edition of a Cloud web service to the current lineup allows you to dedupe, household, and fuzzy match into any aspect of your…

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Melissa Data Continues Globalization of Core Product Line, Enhances MatchUp Tool with International Capabilities

Consolidating duplicate international customer records is now easier than ever with our enhanced MatchUp tool. MatchUp - Melissa Data's deduplication solution - can now parse addresses worldwide, a process that recognizes vast differences in international customer data fields and how they are merged into a data warehouse. Its initial global functionality will handle data for Australia, Germany, and the U.K.…

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Managing Unique Customer Identities with Master Entity Indexes

By David Loshin In the past few entries in this series we have basically been looking at an approach to understanding customer behavior at particular contextual interactions that are informed by information pulled from customer profiles. But if the focal point is the knowledge from the profile that influences behavior, you must be able to recognize the individual, rapidly access…

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Melissa Data’s MatchUp for SQL Server Effectively Solves Business Challenge of Duplicate Customer Data

Data Quality Tool Consolidates Duplicates into Single Golden Record of Customer Data; Uniquely Determines Most Accurate Information Based on Objective Data Quality Score Rancho Santa Margarita, CALIF- April 23, 2014 - Melissa Data, a leading provider of contact data quality and integration solutions, today announced new matching and de-duplication functionality in its MatchUp Component for SQL Server Integration Services (SSIS),…

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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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