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Featured
See How Keebo’s Autonomous Warehouse Suspension Algorithm Maximizes Snowflake Savings
Snowflake warehouse auto-suspend is effective at reducing credit consumption and costs. With Keebo’s real-time controller, it works even better.
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Snowflake vs. BigQuery: What are the differences & which should you choose?
If you’re considering choosing Snowflake vs. BigQuery as your data cloud layer, here’s a comprehensive rundown of the differences of each platform.
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Keebo Wins AI-Based Snowflake Cost Optimization Solutions of the Year
We’re thrilled to announce that Keebo has been recognized as AI-Based Snowflake Cost Optimization Solutions of the Year by CIO Review.
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How Retailers Can Optimize These 5 High-Demand Cloud Data Workloads
Modern retailers require use of large, complex datasets that increase cloud costs & hurt performance. Here’s how to optimize these high-demand workloads.
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Snowflake vs. Databricks: 2025 Comparison + Buyer’s Guide
If you’re building, expanding, or updating your data architecture in 2025, take advantage of this Snowflake vs. Databricks comparison guide.
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Designing a Reinforcement Learning Pipeline: Crafting the Reward Function and Simulator
Learn how Keebo designs RL components to enable autonomous optimizations that reduce cost without hindering performance.
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Snowflake Pricing, Explained: A Full Breakdown of Costs + Savings Opportunities for 2025
Snowflake pricing can be tricky to get your head around, especially when you’re looking to get costs under control. Here’s our comprehensive guide for 2025.
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Snowflake, AI, & Data Infrastructure: 4 Predictions for 2025
Discover key Snowflake trends for 2025, including AI breakthroughs and cost-saving strategies to optimize your data infrastructure and boost efficiency.
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Automated Data Cloud Optimization for Fintech: It’s Less Risky than You Think
Automating your Fintech data cloud optimization doesn’t have to expose you to undue risk. Here are three strategies to mitigate that risk.
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To Succeed In 2025, Data Engineers Need to Become More Lazy!
Insights on new ways that data engineers offload difficult tasks to AI-enabled tools, allowing them more bandwidth for high-level thinking and decision making.