It’s no surprise to anyone who works with data—it’s messy. In every industry and every business, there are data anomalies and issues that can impact the story data tells. If we have any hope of ...

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...

Consumers who don’t have enough of a credit history can suffer from having “thin” credit scores and profiles, which can negatively affect their chances of getting a loan, mortgage, credit card and ...

Health plans have been pouring resources into data analytics for years. They’ve mapped chronic disease trends, pored over prescription data, and chased cost-savings across every corner of the ...

So many retail challenges hinge on unreliable product data. Can agentic AI clean up that data enough to make a difference? Can it do the same for other verticals? Every vertical has its own unique ...

Why does the supply chain that served you so well yesterday seem designed to end your company today? Don’t be surprised; that’s how nature works. Yesterday’s design is optimized for yesterday.

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If your dataset is so voluminous, or it arrives at such high velocity, or it contains such great variety, that you must reimagine the way you use it—you have a big data problem. Google, for example, ...