What is “Data Cleansing”? This is a broad term that can refer to many tasks, all with one goal:  streamline data to ensure its accuracy, completeness, and usability.  Some of the most common data cleansing tasks include:

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• De-duplicating data

• Consolidating vendor, supplier, or customer lists into one “golden” record per entity

• Merging disparate data bases when there is no common linkage key

• Standardizing data, such as changing the word “Boulevard” to “Blvd” to increase match rates

• Parsing out data using text mining to make it actionable and queryable

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Our fuzzy-matching algorithms are all developed using SAS software, one of the most flexible and powerful data analytics platforms in the market.

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