Your data platform is burning money in three places right now. You’re probably only looking at one.
Your platform team tracks latency. They track uptime. They track error rates. But cost? That’s “finance’s problem.”
This is why cloud bills spiral. Nobody’s treating cost as a quality metric. Full-refresh jobs running daily when incremental would do - that’s not a billing issue, that’s an engineering quality issue. Warehouses auto-scaling to XL at 3am for 200 rows - same thing.
The three leaks: compute (30-40% savings from right-sizing and incremental loads), storage (30-50% savings from hot/warm/cold tiering - 80% of your data hasn’t been touched in months), and queries (analysts running SELECT * on billion-row tables because nobody considered appropriate data modelling).
The third one compounds. Bad queries trigger auto-scaling, which inflates compute. One undisciplined pattern cascades through the whole bill.
When we added cost per pipeline to this client’s engineering dashboard - right next to latency and freshness - behavior changed within weeks. Engineers started optimizing because they could see the impact. Cost became visible, so it became someone’s problem.
When’s the last time you audited your cloud data costs line by line?