MatchUp Now Available in the Cloud

Blog Administrator | Data Management, Data Matching, Data Quality, Data Quality Components for SSIS, Duplicate Elimination, SSIS | , , , , ,

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.


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 network that can communicate with our secure servers using common
protocols like XML, JSON, REST or SOAP.
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Melissa Data Continues Globalization of Core Product Line, Enhances MatchUp Tool with International Capabilities

Blog Administrator | Address Quality, Data Matching, Data Quality, Global Address Verification, Global Data Quality | , , , ,

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. with additional countries to follow.
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Managing Unique Customer Identities with Master Entity Indexes

Blog Administrator | Address Quality, Analyzing Data, Analyzing Data Quality, Customer Identities, Data Integration, Data Management, Data Matching, Data Quality, MDM | , , , , , ,

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 that individual’s profile, and then feed the data from the profile into the right analytical models that can help increase value.… Read More

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

Blog Administrator | Address Quality, Analyzing Data, Analyzing Data Quality, Data Quality, Data Quality Components for SSIS, Duplicate Elimination, Golden Record, SQL Server Integration Services, Survivorship | , , , , ,

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), uniquely solving the business challenge of duplicate customer data.… Read More

Entities and their Characteristics

Blog Administrator | Analyzing Data Quality, Data Quality, Fuzzy Matching, Record Linkage | , , , , ,

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? That is the topic of this next set of entries.
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