21 Ways to Reduce Your Cloud Data Warehouse Costs

Nowadays, data leaders are tasked to do more, more, more with less, less, less. More data products with less time. More “strategic initiatives” (generative AI, anyone?) with less resources. And, of course, more cost cutting, particularly when it comes to your cloud warehouse spend.

So, what is a cost-conscious data leader to do? We have you covered. In our latest ebook, we outline 21 practical ways to cut down on warehouse spend across 5 major warehouse and lakehouses – Snowflake, Databricks, BigQuery, and others – across four key areas: warehouse size optimization, table optimization, limiting warehouse access, and query optimizations.

Tips and tricks include:

  • Setting resource and volume monitors
  • Tracking virtual warehouse usage
  • Limiting data editing while prioritizing data compression
  • Leveraging auto-scaling
  • Investing in query performance dashboards
  • And much more!

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