Colleen Quinn

Product Marketing, Dremio Sonar

Colleen Quinn is the Principal Product Marketing Manager for Dremio Sonar. She’s spent more than 15-years working across the analytics lifecycle, from data warehousing and  big data,  to data lakes, cloud analytics, and, now, the data lakehouse.

Colleen Quinn's Articles and Resources

Blog Post

What’s New in Dremio: New Gen AI Data Descriptions and a Unified Path to Iceberg with Dremio v24.3 and Dremio Cloud.  

The Dremio Unified Analytics Platform brings your users closer to the data with lakehouse flexibility, scalability and performance at a fraction of the cost.  We’re excited to show you some new things we’ve been working on to help you analyze your data faster and easier than ever, no matter where it’s stored. We’ve launched AI-powered […]

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Gnarly Data Waves Episode

What’s new in Dremio: New Gen-AI capabilities, advances for 100% query success, plus now on Azure

Transcript Note: This transcript was created using speech recognition software. While it has been reviewed by human transcribers, it may contain errors. Opening Alex Merced: Well, with no further ado, let’s begin with today’s adventure, and we’re gonna be talking about what’s new in Dremio, which includes new generative AI capabilities, advances for 100% query […]

Learn what’s new in Dremio - and how you can accelerate self-service analytics at scale - including new Gen AI capabilities, Dremio Cloud SaaS on Microsoft Azure, advances to ensure 100% query reliability, and expanded Apache Iceberg capabilities to streamline…
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Gnarly Data Waves Episode

Your Lakehouse Just Got Gnarlier: What’s New in Dremio, including Next Gen Reflections

Learn what’s new in Dremio - and how you can accelerate self-service analytics at scale - including Generative AI text-to-SQL capabilities, even faster analytics and better query performance, our new native Apache Iceberg catalog, Arctic, and more.
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Gnarly Data Waves Episode

Simplify data governance at scale across all your data

Learn about the benefits of versioning in integrating and deploying new data, and the differences between file, table and catalog versioning.
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Enable the business to create and consume data products powered by Apache Iceberg, accelerating AI and analytics initiatives and dramatically reducing costs.