Data enrichment is a general term that refers to processes used to enhance, refine, or otherwise improve raw data. … A common data enrichment process could, for example, correct likely misspellings or typographical errors in a database through the use of precision algorithms” (Techopedia). “Brands do this to enhance the data they already possess so they can make more informed decisions. All customer data, no matter the source, begins in its raw form. … Data enrichment makes this raw data more useful” (Redpoint Global). “The goal of enriching data is to make it a more valuable asset — to get more out of it, to do more with it, to access it more easily, and to be more proactive in its use — all without noticeably increasing costs or risks” (Paragon). “As you can imagine, changing source data runs counter to most integrators’ instincts. And yes, it’s risky. Operations that automatically match, correct, or interpolate data values operate with some ‘confidence’ level, meaning that sometimes they are wrong” (CapTech).

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