Are you struggling to predict and control Snowflake costs? You're not alone—accurate forecasting of cloud costs remains a significant challenge for 80% of data management experts (Forrester). Join us for this session in our Weekly Walkthrough series, "Controlling Cloud Costs," where we'll explore how to remove the guesswork from forecasting costs in Snowflake. You’ll gain invaluable insights into transforming your approach to cost management from reactive to proactive. With Unravel's Data Actionability Platform, you can forecast costs precisely and take immediate action to optimize spending.

Integrating Tableflow and Iceberg tables streamlines the process of linking to external data lakes and data warehouses. Jeffrey Johnathan Jennings of signalRoom explains how this approach accelerates time to insight while ensuring a more efficient and cost-effective data architecture.

Find the full podcast interview here: https://youtu.be/c95B1arxZlU

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In highly regulated industries like healthcare and energy, a lot is at stake if an AI system “fails” – therefore leading to a higher risk of unintended consequences that could mean life or death. These high-risk environments can teach us a lot about responsible AI, practical guardrails, and best practices overall. One of those lessons? Make AI “boring”. To dive into what that means for highly regulated industries and beyond, we’re joined by Cal Al-Dhubaib. Cal is the Head of AI and Data Science at Further and founder of Pandata (which was acquired by Further in 2024).

How have data lakes evolved over time, and what do open table formats and catalogs mean for the future of data lakes? In this roundtable discussion, George Fraser, CEO and co-founder of Fivetran, and Dan Lynn, VP of Product for Databases and Destinations, share their thoughts with host Niamh O’Brien about the future of data lakes and how Fivetran is preparing for it. Key highlights;