Fix Your Data Platform Costs Before It's Too Late

How to Cut Data Platform Costs on Snowflake, Databricks & BigQuery with FinOps and Autonomous AI Optimization Data platform spend has exploded from 5% to 30–50% of the total cloud bill, and most teams have no idea where the waste is hiding. In this FinOps Weekly interview, Kunal (CEO of Unravel Data) breaks down why data FinOps is completely different from cloud FinOps, how query inefficiency silently burns millions, and how autonomous AI agents are closing the execution gap for enterprise data teams at scale. 00:00 - Intro & Guest Presentation 01:02 - Why Data Platform Spend Has Exploded to 30–50% of Cloud Bills 02:05 - Data FinOps vs. Cloud FinOps: Key Differences 03:17 - How Query Inefficiency Drives Massive Cost Waste 04:48 - The Scale Challenge: Petabytes, Millions of Queries & Non-Expert Users 06:55 - Visibility in Business Context: Attributing Costs to Users & Workloads 08:27 - Detecting Inefficiencies & Prioritizing by Financial Impact 10:22 - Why Developers Are Not Incentivized to Optimize Cost 11:07 - Performance and Cost as Two Sides of the Same Coin 12:13 - Explaining Problems in Plain English to Close the Knowledge Gap 14:03 - The FinOps Execution Gap: From Insight to Action 15:02 - Autonomous Enforcement: Human-in-the-Loop vs. Fully Autonomous 16:25 - The Watchdog: Validating Fixes and Protecting SLAs 17:34 - AI-Powered Code Rewriting and Why LLMs Alone Are Not Enough 19:22 - Integrating with GitHub for Shift-Left Cost Prevention 20:39 - Infrastructure Optimization: Dynamic Cluster Sizing in Snowflake & Databricks 22:30 - Interactive vs. Job Clusters: A Hidden 4x Cost Mistake 24:03 - AI Workloads on Data Platforms: The Next Cost Explosion 27:51 - Persona-Based Autonomous Agents for FinOps, DataOps & Quality 31:29 - Building the Full-Stack Data FinOps Product 32:16 - Wrap-Up & Final Thoughts