• April 23, 2014

Melissa Data Launches MatchUp for SQL Server

Melissa Data, a provider of contact data quality and integration solutions, today announced new matching and de-duplication functionality in itsMatchUp Component for SQL Server Integration Services (SSIS), solving the business challenge of duplicate customer data.

Based on proprietary logic from Melissa Data, a CRM magazine 2013 Service Leader, MatchUp determines the best pieces of data to retain versus what to discard, consolidating duplicate records. By assessing the quality of individual data fields, MatchUp enables database administrators (DBAs) to determine the best customer contact information in every field.

MatchUp works in sharp contrast to matching and de-duplication methods that rely solely on subjective principles, such as whether the record is the most recent, most complete, or most frequent. Instead, selection criteria for determining a golden record is based on a relevant data quality score, derived from the validity of customer data, such as addresses, phone numbers, emails and names. Once the golden record is identified, MatchUp further references the data quality score during survivorship processes to support creation of an even better golden record; duplicate entries are then collapsed into a single customer record while retaining any additional information that might also be accurate and applicable.

Using deep domain knowledge of names and addresses, survivorship operations with MatchUp can granularly identify matches between names and nicknames, street/alias addresses, companies, cities, states, postal codes, phones, email addresses, and other contact data components.

"The average database contains eight to 10 percent duplicate records, creating a significant and costly business problem in serving, understanding and communicating with customers effectively. The ideal is a single, accurate view of the customer—known as a golden record, yet this remains one of the biggest challenges in data quality based on methodologies that don't adequately evaluate the content of each data field. As a result, DBAs either overlook duplicates or consistently struggle with determining what information survives in the database and why," said Bud Walker, director of data quality solutions at Melissa Data, in a statement. "By using intelligent rules based on the actual quality of the data, DBAs are much better positioned to retain all the best pieces of information from two or more duplicate records into a single, golden record that provides valuable insight into user behavior and helps boost overall sales and marketing performance."

The MatchUp tool isn't the first item Melissa Data has launched for the SQL Server architecture. Just this past September it launched  Community Editions of Data Quality Components for SQL Server.

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