Because we spent the planning phase building and testing our accelerators internally, we aren't starting from zero. We are starting with a validated engine. We aren't guessing if our Near-Real-Time Data Hub approach works—we’ve already seen it run in our lab.
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That’s how a lot of our first calls begin. Prospects want to talk tech: lakehouse vs. warehouse, dbt vs. Informatica, …
Modern BI tools promise a lot — faster insights, cleaner visuals, empowered users. But here’s the truth from the trenches: BI adoption fails when tools come before trust.
Many organizations try data governance and watch it fizzle. Here's what actually makes it stick—and why tools alone won't get you there.
Introduction: Avoiding the AI Pitfalls The final part of our AI adoption series focuses on how to implement AI strategically. …
This blog, part 2 of our series, outlines practical AI applications in data analytics across business functions that strategic organizations can start using today.
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