Webinar: We tried talking to our data - here’s what’s actually working (and what’s not)

Will Hayes•30 January 2026•1 min read

In this 30-minute session, we unpacked what we had been experimenting with using Google’s conversational AI to spend less time wrangling data and more time actually learning from it. In this quick, practical session, we explored what we had learned regarding:

  • Natural language to SQL in BigQuery - What worked, what didn't, and the validation checks we utilized.
  • BigQuery metadata experiments - What we tested and what actually mattered in practice.
  • Looker Studio conversational analytics - Quick wins for ad-hoc charts and where the technology still fell short.
  • Testing with Colab notebooks - How we refined instructions and knowledge bases before going live.
  • Deploying conversational agents - Team self-serve implementations in Slack/Teams and Looker Studio integrations.

This session covered where conversational analytics helped, where it still broke, and the validation checks we employed - providing practical takeaways that could be tested immediately.

Have questions? Reach out to us.

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