A major trend across industry and public sectors is the growing role of artificial intelligence within an enterprise digital transformation strategy. AI is already providing order of magnitude improvements with traditional enterprise use cases like fraud detection, predictive maintenance, recommendation engines, yield optimization, churn reduction and others.
A successful enterprise AI initiative will spawn hundreds if not thousands of use cases, each supported by a narrowly defined algorithm. Once that’s understood and anticipated, it’s evident that large enterprises need a common data foundation to scale their AI ambitions. Symptoms include hundreds of silos of replicated data. These silos incur hidden costs, add to mounting technical debt, restrict agility and pose barriers to operationalizing insights. Left unchecked, these silos can spread exponentially as a result of proliferating vendor tools and easy-to-spin-up cloud offerings.
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