The problem
Every new dashboard, customer report, or AI pilot re-implements revenue, margin, and active users slightly differently. The data team spends its time reconciling numbers instead of improving them.
How Datafor helps
- One analysis model per domain with relationships, hierarchies, measures, and time intelligence. Semantic modeling →
- Certified metrics in the Metrics Library, with drift checks that flag measures whose logic no longer matches the definition.
- Governance once: row policies and column hiding defined on the model apply in every report, embed, API call, and AI answer. Governance →
- AI grounded in your model: business terms and synonyms help the AI Agent map questions to the right fields, and every answer shows the query it ran. AI Agent →
- Diagnostics in the model designer catch duplicate or stale bindings before they reach users.
What changes
- Business users explore and ask questions on their own, inside the guardrails you set.
- Definitions change in one place and propagate everywhere.
- Access reviews look at one policy set, not one per tool.