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Data Matching and Entity Identification at Scale

Data matching is the task of identifying, matching, and merging records that correspond to the same entities from several source systems. These entities may be people, places, publications or citations, consumer products, or businesses. The major hurdle that encounters while solving this problem is lack of common entity identifiers, easily available information like name, address, etc. that may change over time is usually of low quality and produce poor results with high error rate. Technological advancements in the last decade have made it possible to scale data, matching on large systems that contains millions of records and improved accuracy. You can read more at :

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Three Stages of Big Data Collection Methodology
From Big Data to Small Data 


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Saturday, 19 September 2020
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