dbt accelerates trusted data workflows with its Fusion engine, delivering faster, governed AI analytics at scale. It offers automation, rich lineage, and cost efficiency for reliable data development.
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dbt is recommended for data teams and professionals who want faster, trusted, and governed data workflows to improve quality, reduce costs, and build reliable AI. Companies like Snowflake and Databricks trust dbt to accelerate analytics and deliver real AI impact.
dbt offers a free Developer plan with one seat and up to 3,000 models per month, plus a Starter plan at $100 per user/month for five seats, 15,000 models, and 5,000 queried metrics monthly. Enterprise and Enterprise+ plans provide custom pricing, support up to 100,000 models monthly, allow more projects, and include advanced features like dbt Canvas, security controls, and priority support. All paid plans add API access, enhanced security, and greater release track access, scaling to meet larger teams and complex deployments.
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Implementing dbt involves signing up and connecting your data platform, which typically requires basic configuration like setting up data connections and initial project settings. From there, you can customize workflows and models as needed for your team, generally taking a few hours with available documentation.
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