Systems | Development | Analytics | API | Testing

ThoughtSpot June Release: Customize Your Agent

Check out what’s new in ThoughtSpot’s latest release! SpotterModel gets smarter: Build complex data models with AI formula suggestions and instant version rollbacks if you make a mistake. No stress, no lost work. Spotter Instructions: Fully customize Spotter’s persona, formatting rules, and strict guardrails. It says exactly what you want it to say—and nothing it shouldn't. Ad Hoc Analysis: Drop local files directly into Spotter for instant answers, or blend them safely with your governed enterprise data.

How to Architect a Clean Context Layer for Trustworthy AI

A CFO asks her AI agent a simple question: "What was our ARR at the end of Q3?" The agent finds the subscriptions table, spots a column called arr, sums it up, and returns $16.4M. Strong quarter. Everyone nods. The real number was $13.9M, but no one in the room knew it yet. I hear some version of this story from nearly every data leader I talk to right now, and it almost always starts the same way. They stand up an AI pilot. It looks sharp in the POC.

data:unplugged 2026 Recap - PAYBACK's Decade of Data Mastery

At the recent data:unplugged 2026 in Münster, Europe’s biggest festival for data and AI, the stage was set for a masterclass in data transformation. Julian Stock, Analytics Reporting Team Lead, and Andreas Weiß, Senior Reporting Engineer, from PAYBACK, Germany’s premier loyalty program, shared the stage to detail a decade-long evolution: the journey from a strict, ticket-based reporting system to a thriving, AI-ready data culture.

Spotter Enhancements

Spotter just got smarter and more in your control. You can now customize your agent's name, persona, output formatting, and guardrails to dictate exactly how it should (and shouldn't) handle data. Set it once, in plain language, and every user across the organization gets a configured, governed Spotter. Other new features include: Ad-hoc file analysis: Upload any flat file directly into Spotter and start asking questions instantly, solo or blended with your governed data.

How Booking.com Scaled Agentic Analytics for Self-Service

At Snowflake Summit '26, Chris de Groot, Manager of Data Engineering Customer Service, and Jay Stricks, Group Product Manager, Insights Platform, took the stage to share Booking.com's massive data transformation. In their session, "Booking.com's Data Travels: Platform Foundations to Agentic Analytics," they laid out a masterclass on how to make a colossal, fragmented data landscape entirely AI-ready.

The internal war over who owns AI.

There is a massive boardroom fight happening right now over who gets to control AI. Should it be IT? A centralized lab? The executives? Boris Rabkin from Ligentia drops a truth bomb: AI belongs wherever value is actually created. If your AI strategy is locked inside an isolated corporate lab instead of in the hands of your product, engineering, and customer teams, it’s going to fail. Full episode out now!

Stop Rebuilding Data Models From Scratch: Meet SpotterModel

Your data engineering team shouldn't be the bottleneck between a business question and a governed answer. SpotterModel turns a natural language prompt into a deployable data model. This release does the heavy lifting on complex calculations, and lets you roll back to any previous model state, anytime, so a bad change never costs you hours of rebuilding. It maps your relationships, dimensions, and measures instantly, and you stay in control of table selection and the build process the whole way.

Build Your Super Team: What 150 Years of Soccer Data Says

Soccer is a game of stories, but the most fascinating stories are often buried deep inside the numbers. And this year on the world's biggest stage, the tournament has expanded by nearly 60% – traditional scouting reports and pundit hot-takes simply can't keep up with the sheer volume of new data. That’s why we’re looking at the tournament through a much wider lens.