I would focus on optimizing existing resources by regularly assessing data requirements and eliminating redundancies to reduce storage and processing costs. I would also explore open-source or cost-effective alternatives for data management tools that offer the required functionality without high licensing fees. Additionally, I would prioritize scalable solutions that allow for gradual growth, enabling us to manage costs effectively by expanding resources incrementally rather than committing to large upfront investments. I am sure, this approach will ensures efficiency, sustainability, and flexibility within budget constraints.

Managing data warehouse costs isn’t about cutting corners—it’s about smarter investments. We optimize costs through data tiering, pay-as-you-go models, and query optimization. Data rationalization has been key—consolidating access instead of duplicating data across multiple downstream systems reduces storage costs and improves consistency. We also focus on identifying stale data—archiving or decommissioning unused datasets frees up resources for what truly matters. Thanks to everyone for sharing their insights! What’s been your biggest cost-saving win in data management?

Two questions: 1. Provisioned or Serverless like BigQuery, Snowflake etc, 2. Do you have RBAC set up to know who, which tables and what query was run and the cost or time for these queries? Now that you know the cost model and where your costs are being spent, you can now: - speak to users and developers about their usage, - you can prioritize systems and queries that need to be optimized, - you can triage what tables need clustering, table storage billing model selection, partitioning, zero-copy (CoW) clones.... and, - you can also understand and justify the USAGE and UPLIFT of these costs in your business! NEVER forget about the VALUE of what you've created!

To manage data warehouse costs effectively while maintaining performance, consider the following strategies: Cost Management Strategies for Data Warehouses: Optimize Resources:?Assess essential data, purge redundancies, and use compression. Efficient Tools:?Explore open-source or scalable platforms with pay-as-you-go pricing. Query Efficiency:?Use partitioning, indexing, and caching to speed up queries. Monitor Usage:?Regularly audit and adjust resource allocation. Scalable Solutions:?Invest in platforms that grow incrementally with your needs.

It’s important to avoid the “I need it all” mindset. Data retention – and expiration – policies are key not only to keeping costs down, but also to maintaining compliance with company and/or legal policies.