Discover Astrato's semantic layer upgrade: Business Questions, Set Filters, Time Intelligence and Grouped Dimensions for reusable analysis.
Astrato connects to your existing Snowflake Semantic Views, extends them, puts them to work across analytics, AI and action, and publishes supported work back to Snowflake.
Did you know you can add Snowflake GenAI Insight Summaries powered by Snowflake (and table/view reporting) to Slack & Teams, directly using Snowflake?
Snowflake’s powerful platform is architecturally different from almost every traditional database system and cloud data warehouse. Snowflake has completely separate compute and storage, and both tiers of the platform are near-instantly elastic.
Looking for Omni Analytics competitors in 2026? Compare the 8 best Omni Analytics alternatives including Astrato, Looker, Sigma, and Hex for modern BI.
Looking for ThoughtSpot competitors in 2026? Compare the 9 best ThoughtSpot alternatives including Astrato, Power BI, Tableau, Sigma, Hex, and more.
Two reports can use the same customer segment and produce different results. Learn how reusable Set Filters keep customer qualification logic consistent.
AI can answer business questions, but what happens next? Learn how Astrato Business Questions turn useful analysis into reusable definitions.
Databricks AI/BI now embeds dashboards externally. So when do you still need a third-party platform? A decision guide for data platform teams.
Compare embedded analytics platforms for BigQuery — Astrato, Sigma, Looker, Looker Studio, Power BI, Metabase. Built for product teams in Slack.
Self-service BI keeps breaking. Guided self-service fixes it: the data team designs the path, business users move freely within it. Here's how.
Every BI vendor claims self-service in 2026. A four-level spectrum, five evaluation questions, and an honest comparison of the platforms that compete on Snowflake.
Learn what MCP means for business intelligence and how Claude or ChatGPT can work with Astrato's business definitions and live warehouse data.
Learn how Snowflake Semantic Views help AI assistants use trusted business definitions, reduce inconsistent answers and power AI-driven analytics.
Explore what Claude does well in data analytics, from SQL to insights, and why trusted business definitions, live data and access controls matter.
Learn why AI assistants need row-level security, user permissions, and governed data access to deliver accurate answers without exposing restricted data.
When does a dashboard stop being enough? Learn when recurring business decisions need an app built around scenarios, actions, and outcomes.
Why can two AI tools query the same warehouse and return different revenue numbers? See how business definitions turn raw data into answers you can trust.
AI can now change measures and data models, not just query them. See how a governed semantic layer keeps AI-made analytics changes under control.
Version control, validation, lineage and MCP in one governed semantic layer — so the numbers your team builds with AI agree with the numbers on your dashboards.
