Metabase Data Studio
Build the semantic layer that makes AI analytics trustworthy
Metabase Data Studio launched on March 31, 2026 with 153 votes, #228 of 23,380 launches that month and more than 95% of that year's launches.
What it does
AI analytics is only as good as the context you give it. Without a semantic layer - a unified, shared definition of metrics, segments, and business logic - AI (and everyone else) is guessing at what "active user" or "revenue" means at your company. Data Studio is the analyst workbench where that foundation gets built. Define metrics once. Transform raw tables using SQL or Python. See dependencies before changing anything. Publish what's trusted to your Library. Then get reliable answers from AI
Wrangle your data, add context, and define metrics once for a governed semantic layer people and AI can query reliably. Get end-to-end visibility into every change in Data Studio.
Wrangle your data, add the context it's missing, and define metrics once so your teammates and AI can query reliably and get the right answer. Get end-to-end visibility: make a change, see what breaks before you ship it. Data Studio is where you shape the data your analytics depends on — a unified computational graph of tables, transforms, reusable metrics, business logic, and lineage. Clean, join, or pre-aggregate data in SQL or Python and create a new, persistent table for teams and agents to explore and ask questions. Rename columns, add descriptions, and set semantic types so a table means something to the next person (or agent) who opens or queries it. Save aggregation logic as a…from metabase.com
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Metabase, an open-source business intelligence tool2015 · metabase.com · ▲287Metabase grounds every answer in your semantic layer — your metrics and business logic — so you can inspect the query behind it.
Skills Marketplace by DataboxJun 2026 · databox.com · ▲427Ready-made AI analytics skills for your business data
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