Make data make sense with the Semantic Layer
Our built-in semantic layer bridges the gap between raw cloud data and business-ready insights. Define logic, metrics, and relationships once – then reuse them across every dashboard, user, and use case.
Built differently for accuracy, not shortcuts
❌ Every dashboard defines metrics differently
❌ Business users get conflicting answers
❌ Analysts waste time rebuilding logic
✅ Define reusable measures, dimensions and joins
✅ Empower self-service without losing control
✅ Standardize KPIs across teams and tools
Centralized AI-acclerated metric definitions
Define your most important KPIs once – like ARR, conversion rate, or churn – and use them everywhere. Maintain consistency across dashboards without rewriting calculations.
Business-friendly data modelling
Make your data easier to explore by abstracting away technical joins and raw field names. Build logical, human-readable models that business users actually understand.
Built-in governance
Your semantic layer respects the data warehouse. Row-level security, access rules, and roles are enforced automatically, ensuring nothing slips through the cracks.
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AI-ready data structure
Well-defined models help AI understand your data. That means better answers from natural language queries and more accurate insights from AI-powered analysis.
Performance at scale
Because Astrato is live-query and zero-copy, your semantic layer is sitting directly on top of Snowflake, BigQuery, Databricks or any other cloud data warehouse. So whether you have 10 or 10,000 users, performance is dictated by the speed of your warehouse – typically instantaneous. There’s no syncing, caching or stale definitions.
Transparent and easy-to-inspect definitions
Every metric in Astrato can be inspected. Users can see exactly how it’s calculated, helping you avoid hidden black-box dashboards. Plus, with tools like our Custom Report, end users build on top of governed metrics, not raw tables, keeping things clean and transparent.