There are customer records in this data that are semantic duplicates, that is, they represent the same user entity, but have different labels or values. ![]() This problem particularly impacts companies trying to build accurate, unified customer 360 profiles. These sources are often related but use different naming conventions, which will prolong cleansing, slowing down the data processing and analytics cycle. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. ![]() Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. ![]() In today’s digital world, data is generated by a large number of disparate sources and growing at an exponential rate.
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