Live Webinar

The AI Hype: How to build the data foundation that makes AI work

Wednesday, August 19, 2026

9 AM PST | 12 PM EST

Nathan Loding, Developer Advocate, Matia
Brittany, Head of Data & Analytics, Drata

Everyone wants to deploy AI. Far fewer organizations have the data foundation required to make AI reliable, scalable, and useful.

Many teams jump straight to copilots and AI agents only to discover fragmented pipelines, inconsistent data quality, missing business context, and disconnected tools become the biggest obstacles, not the AI models themselves.

In this webinar, Data Culture and Matia will walk through a practical framework for evaluating AI readiness and discuss what it actually takes to build a modern data foundation for AI initiatives.

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What We’ll Cover

Why good pipelines alone aren't enough even when pipelines are running and data is moving, it can still be stale, incomplete, or inconsistent, and without the necessary context, AI lacks the “why” behind the data it consumes, leading to unreliable outputs.
The risk of silent data failures: Issues often go undetected until they’ve already impacted downstream systems, analytics, or AI outputs.
The impact of fragmented tools Disconnected systems create inconsistent results, with no unified view of data quality, lineage, or downstream impact.
How Drata uses Matia to monitor data freshness, schema changes, and pipeline health—ensuring reliable data for downstream AI and analytics

Who is this webinar for?

If you’re building AI initiatives or preparing your data systems for AI, this session will help you understand the foundational gaps that hold most teams back—and what it takes to fix them.

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Meet the Speakers

Get to know the experts who will be leading the event.

Nathan Loding, Data Advocate, Matia

Nathan works as a Data Advocate at Matia, working to enable data engineers and architects. He comes from a full-stack engineering background, specializing in data and accessibility across both large enterprise and bespoke small business solutions. He is a regular conference speaker, and co-organizer of the KidzMash family track of CodeMash.

Matthew Shump, Head of Data & Analytics, Drata

Matthew is currently the Head of Data & Analytics at Drata, where he leads the company’s data and analytics strategy. Prior to Drata, he served as VP and Head of Data Engineering, Analytics, and Data Science at Vimeo, overseeing a global team of engineers, analysts, and data scientists supporting infrastructure, experimentation, machine learning, reporting, and customer-facing data initiatives.He has also advised numerous early-stage startups across the data, analytics, and AI ecosystem and previously co-founded Watchtower AI. With deep expertise spanning data engineering, analytics, AI, and scalable infrastructure, he brings extensive experience helping organizations build modern, data-driven systems that power business operations and AI initiatives.