dbt Labs, the pioneer in analytics engineering, announced dbt Cloud enhancements designed to help businesses turn data into a competitive advantage. As companies’ data volumes explode and the need for trustworthy, high-quality data increases, dbt Cloud is meeting the market need for streamlined data transformation across pipelines, workflows, and teams.
“Accurate and timely data is crucial, which is why we’ve delivered a standardized way to quickly build reliable, holistic, and high-quality data pipelines at scale,” said Luis Maldonado, VP of Product at dbt Labs. “These new features take this even further, significantly improving data workflows and AI workloads, all while empowering more users with powerful business insights.”
Improve the way data teams build, test, and ship high-quality data pipelines
dbt Cloud includes a host of enterprise capabilities for delivering trusted data quickly, securely, and affordably. New features include:
- dbt Assist: An AI-powered copilot experience, dbt Assist automatically generates documentation and tests to let data developers get more done in less time (beta).
- Advanced CI: A new “compare changes” view lets teams verify that changes to the codebase meet quality expectations before they are merged into production (beta coming soon).
- Unit testing: A new feature that allows teams to improve test coverage without driving up data platform spend through earlier validation of modeling logic (generally available).
- dbt Cloud CLI: Offers developers the flexibility to contribute to projects in dbt Cloud through their terminal or IDE of choice (generally available).
Seamlessly trace and orchestrate data pipelines in more platforms
Data teams rely on dbt Cloud as a control plane to catalog, orchestrate, govern, and observe their end-to-end data workflows. New platform enhancements and integrations give dbt Cloud even more context into the dashboards and decisions that dbt models power. New capabilities include:
- Automatic exposures: Gives dbt Cloud automatic awareness of Tableau dashboards downstream of dbt models, allowing users to trace and automate end-to-end data lineage to unlock efficiencies, optimize compute costs, and improve data freshness and trust. Auto-exposures are incorporated throughout dbt Cloud including in dbt Explorer, orchestration workflows, and CI jobs (beta coming soon).
- Microsoft integrations: dbt Cloud now supports Microsoft Azure Synapse (preview) and Microsoft Fabric (generally available).
SOURCE: PRNewswire