dbt Labs × Bilt Rewards
dbt Labs x Bilt Rewards, 80% analytics cost cut with the Semantic Layer
80% reduction in analytics costs
Unsustainable per-user costs to scalable, centralized analytics
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Why it works
The case study earns its headline number by tracing it directly to a specific mechanism: moving transformation logic out of a BI embed and into dbt's Semantic Layer with a GraphQL endpoint eliminated per-user pricing at scale. The before-state is concrete, the team size (three analysts, 10,000+ external consumers) gives the constraint real weight. There is a slight coin-flip between Efficiency and New Capability because centralized metric definitions enabled a headless BI approach Bilt could not practically do before, but the headline leads with cost reduction so Efficiency wins.
Steal this
Anchor the before-state in a business model problem, not just a technical one. Framing the villain as per-user pricing that scales linearly makes the cost savings feel inevitable and structural rather than incidental.
Click to enlarge ↗ This is editorial commentary and curation. The case study, screenshot, and all metrics are dbt Labs's published work; we link to the source and lead with our analysis.