The growth of AI in the enterprise, however, has been hampered because data scientists too often have limited access to the relevant data they need to build effective AI models. These data specialists are frequently forced rely solely on a few known sources, like existing data warehouses, rather than being able to tap into all the real-time, real-life data they need. In addition, many companies have great difficulty efficiently and affordably determining the business context and quality of massive amounts of data instantly. Given these difficulties, it’s easy to understand some of the historical barriers to AI acceleration and adoption.
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