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About the Query page betaenterprise

Learn how to query data with the Query page and view documentation in dbt Explorer.

tip

Query page is available in private beta to Enterprise accounts. To join, please reach out to your account manager.

The Query page in dbt Cloud empowers users to seamlessly explore and query data with an intuitive, context-rich interface. It bridges technical and business users by combining metadata, documentation, AI-assisted tools, and powerful querying capabilities into one unified experience.

Query page in dbt Cloud integrates with dbt Explorer, dbt Cloud IDE, Visual Editor, dbt Copilot, and dbt Semantic Layer to make it easier for you to perform exploratory data analysis, leverage AI-assisted tools, make faster decisions, and collaborate across teams.

Overview of the Query page and its featuresOverview of the Query page and its features

Key benefits​

Key benefits include:

  • Quickly write, run, and iterate on SQL queries with tools like syntax highlighting, tabbed editors, and query history.
  • Leverage dbt metadata, trust signals, and lineage from dbt Explorer for informed query construction.
  • Make data accessible to users of varied technical skill levels with SQL, Semantic Layer queries, and visual tools.
  • Use dbt Copilot's AI-assistance to generate or edit SQL queries, descriptions, and more.

Some example use cases include:

  • Analysts can quickly construct queries to analyze sales performance metrics across regions and view results.
  • All users have a rich development experience powered by dbt Explorer's end-to-end exploration experience.

Prerequisites​

  • Have a dbt Cloud Enterprise account — book a demo to learn more about the Query page.
  • Available on all tenant configurations.
  • Have a dbt Cloud developer license with access to the Query page.
  • Configured developer credentials
  • Your production and development environments are on dbt Cloud’s ‘Latest’ release track or a supported dbt version.
  • Configured the Semantic Layer for your dbt project.
  • Use Snowflake, BigQuery, Databricks, Redshift, or Postgres.
    • Note SSH tunneling for Postgres or Redshift connections is not supported.
    • Single sign-on (SSO) for development user accounts supported, however SSO for production credentials not yet supported.
  • Have a successful job run in the environment where you configured the Semantic Layer.
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