Put Your Data to Work with ThoughtSpot in ChatGPT Work
From the source: ThoughtSpot BlogPutting Data to Work Requires Someone to Build for Everyone Every organization says it wants self-service analytics, but very few have it. What actually stalls true self-service analytics is the invisible work that has to happen before anyone can ask a data question: the semantic layer, query engine, security model, and analytics app. That work lands on your product and data teams, who are…
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Introducing ThoughtSpot Spreadsheets on Live Data
View, Work, and Save Your Live, Governed Data, Without Ever Exporting It Every analyst has a version of this “Monday blues.” A leader pings asking for the quarterly forecast, wants it broken out by region, and needs it for a call in thirty minutes. The fastest way to do this? Pull the data out of your tool, paste it into Excel, and build the report there. Thirty minutes later, you've got the…
4 Signs Your AI has a Context Problem, Not a Model Problem
Most AI agents can write SQL. The problem is they write it against the wrong definition of revenue, for the wrong team, using the wrong business rules, and you won't catch that in a demo. Before you evaluate a single semantic layer vendor, there are four things worth getting right first. The semantic layer market has never been more crowded. Every major analytics vendor, data platform, and BI…
From Dashboards to AI Agents: Huel’s Analytics Journey
You’ve rolled out a modern data stack, built self-service dashboards, and empowered your team to ask their own questions. Job done, right? Not quite. The data landscape is shifting rapidly beneath our feet, which makes it critical to understand how to build your AI for BI platform so you can scale and navigate technology evolutions. I had the pleasure of sitting down with Jane Smith,…
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