New Data Quality Tool Supports Single Golden Record of Customer Data

Melissa Data, a provider of contact data quality and integration solutions, has introduced new matching and de-duplication functionality in its MatchUp Component for SQL Server Integration Services (SSIS). Helping to solve the business challenge of duplicate customer data, MatchUp leverages proprietary logic from Melissa Data to determine the best pieces of data to retain versus what should be discarded. By evaluating the quality of individual data fields, MatchUp can provide a consistent method for DBAs to maintain the best customer contact information in every field.

“The average database contains 8 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. "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.”

According to Melissa Data, istead of relying solely on subjective principles, such as whether the record is the most recent, most complete or most frequent, the selection criteria used by MatchUp for determining a golden record is based on a relevant data quality score, established through the validity of customer data such as addresses, phone numbers, emails and names. Once the golden record is identified, MatchUp then references the data quality score during survivorship processes to support creation of an even better golden record; and duplicate entries are then collapsed into a single customer record while also retaining additional information that may also be accurate and applicable.

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

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