Is "Quality" Killing Your AI? Defining Data Fit for Strategic Success
Live Session with Andy Hannah & Malcolm Hawker | February 18th, 2026 @ 1:00 PM EST
Every data investment carries risk unless you know how to measure its “fit” for the mission.
In this live session from Blue Street Data’s Building with Better Data series, Andy Hannah (CEO & Co-Founder, Blue Street Data) and Malcolm Hawker (Head of Data Strategy, Profisee) dive into the controversial reality: data quality isn’t actually the biggest barrier to AI adoption—data fit is.
When data is “high quality” for a BI dashboard but “toxic” for a Large Language Model, organizations face catastrophic model failure, wasted spend, and eroded trust. This webinar will give you the tools to move beyond generic cleanliness and learn how to define, measure, and verify data fit to ensure your AI and analytics models don’t just run—they thrive.
What you’ll learn:
- The “Fit vs. Quality” Framework: How to define “the right data” for specific AI vs. BI use cases.
- Why Models Break: A deep dive into the mechanics of how “good” data for humans becomes “bad” data for machines.
- The Cost of Misalignment: How to calculate the risk of deploying models on data that hasn’t been “fit-tested.”
- Strategic Certainty: Practical steps to align data procurement and preparation with specific business outcomes.
Whether you’re a CDO, AI architect, or analytics leader, this session will help you shift from chasing “clean” data to securing “fit” data, turning your data strategy into a true competitive advantage.
Our Speakers:
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