As Snowflake footprints expand, organizations are under growing pressure to prove value, control spend, and deliver consistent performance. But FinOps dashboards often miss the real problem: not just compute, but waste.
DBTA recently held a webinar, Stop Paying for Bad Data: 7 Hidden Leaks in Your Cloud Bill, with Randy Rouse, field CTO, Quest and Adam Morton, AI-ready data architecture
strategist and founder, Mastering Snowflake, who covered which design choices reduce compute cost and how to avoid runaway prices.
FinOps dashboards typically show usage, not waste, Rouse explained. Every redundant, obsolete or trivial record that lands in your platform gets transformed, written, read, and re-read. Each pass burns credits and erodes trust. According to Gartner, Rouse noted, companies lose more than $12.9 million due to poor data quality.
Without clear ownership and lineage, teams can't see what already exists, so they unknowingly rebuild it. You don't just duplicate storage; you multiply compute with redundant refresh jobs and caches, Rouse said.
To fix this, extend lineage into a universal catalog that spans ETL, Bl, and Al tools. Tie every dataset to an owner and use Al-powered search to help teams find trusted assets before they build.
Every failed job that requires a manual rerun is a direct tax on your cloud bill and your team's productivity. These incidents are frequent and expensive. Implement five-pillar observability: freshness, volume, schema, distribution, and lineage. Alert on anomalies where it matters and wire alerts to dataset owners via your catalog, according to Rouse.
When analysts can't find or trust a source, they make their own data sets and products. This spawns a shadow lifecycle of new jobs, dashboards, and costs for data that likely already exists. Adopt a data-product mindset. Publish certified and trusted data products with clear owners and SLAs in a central marketplace. Use Al-assisted discovery to turn discovery into reuse, not duplication.
The worst leak is the one that nobody owns. Governance aligns everyone on one goal: only trusted, modeled, governed data should consume your most expensive resources. It replaces heroic fixes with measurable accountability: owners, SLAs, and certified products instead of mystery jobs, said Rouse.
Quest supports this strategy by building trusted, high-quality data products through data modeling, intelligence, and governance. Quest’s solutions are platform agnostic for database collaboration and seamless migrations (cloud and on-prem).
For the full webinar, featuring a more in-depth discussion, Q&A, and more, you can view an archived version of the webinar here.