Data strategy: The power of chatting with structured data

[jrineakter]

In an era where data is described as “the new oil,” a refined (pun intended) data strategy is non-negotiable for businesses. As organizations drown in data generated at unprecedented rates, the call for advanced tools to manage it all has never been louder.

That’s why here, in the labs of data.world, we’re going all in on the ability to chat with structured data. What exactly does that mean?

AI tools like ChatGPT allow users to query the vast stores of data on the Web. What if you could apply those same sweeping research and response processes to your own data?

Imagine you’re an insurance company. Instead of asking an LLM, “What is a loss ratio?”, you could ask it, “How do we define ‘loss ratio’ in our organization?” Or, “What is the loss ratio for policies that have been held for less than a year?” Then, you’d get answers based on your unique data. This is contextual LLM responses in real-world scenarios, and it is now a reality.

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The challenge: Overwhelming data, underwhelming insights
Today's businesses face a paradox; while they have more data at their disposal than ever, converting this vast reservoir into actionable insights remains a daunting challenge. Traditional data management tools often fall short in making data accessible and understandable for all, leaving valuable insights buried in the digital deep.

We've been promised the moon with AI, but until now, it's been more like a guided tour of the backyard. Why? Context. Without it, AI is just shooting in the dark. Generative AI's potential has been bottlenecked by its inability to deeply understand and interact with business-specific contexts and structured data.