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Atlan Turns into dbt Semantic Layer Launch Associate and Broadcasts Integration – Atlan

With column-level lineage and dbt metrics as a first-class citizen in Atlan, this partnership will increase context, visibility, and self-service for numerous information groups.

Right now we’re excited to announce our partnership with dbt Labs, the pioneer in analytics engineering. As a part of this, joint clients may have entry to an end-to-end governance framework for information fashions and metrics within the trendy information stack.

dbt Labs’ new Semantic Layer allows organizations to centrally outline key enterprise metrics like “income,” “buyer depend,” or “churn fee” in dbt, and question them in downstream analytics instruments. This enables everybody within the enterprise to really feel assured that they’re working from the identical assumptions as their colleagues, no matter their information tooling of alternative. If a metric definition is up to date in dbt, it’s seamlessly up to date in every single place, making certain consistency all through the enterprise.

Atlan’s integration with the dbt Semantic Layer brings dbt’s wealthy metrics into the remainder of the info stack. With this integration, firm metrics at the moment are part of column-level lineage, spanning from supply programs and information storage to transformation and BI.

360° asset profile for a dbt Revenue metric in Atlan
dbt metrics at the moment are a first-class citizen in Atlan, full with their very own 360° profile the place you may assign house owners, connect sources, confirm metrics, see definitions, write context-rich READMEs, and extra.

We’re excited to companion with dbt Labs to make metrics a firstclass citizen for information groups.

Metrics are the language by which the enterprise understands information. For much too lengthy, information groups have handled limitless chaos about metrics definitions and accuracy.

Now, with Atlan and dbt, numerous information individuals can lower by the chaos and work collectively higher with simpler collaboration and alignment.

Varun Banka, Co-Founder at Atlan

Our native dbt Cloud integration ingests all dbt metrics and metadata about dbt fashions, merges it with metadata from all different instruments within the information stack, creates column-level lineage from supply to BI, and sends that unified context again into instruments like Snowflake and the BI instruments the place individuals work every day.

With this, when questions come up about firm information, information groups can rapidly discover the right metric, backtrack by modifications by way of model management, assess precisely what modified at each layer (i.e. the info, definition, and operational layers), and hint how downstream belongings have been affected. This highly effective affect and root trigger evaluation lastly offers trendy information groups the instruments they want for end-to-end information governance and alter administration at each stage of the info lifecycle.

Lineage graph in Atlan, featuring a dbt transformation and associated context
Transcend tables and warehouses with end-to-end lineage, now with column-level visibility into all of your dbt transformations.

The dbt Semantic Layer offers clients a central supply of fact for his or her business-critical metrics, and the flexibility to question them from instruments like Atlan.

By means of this partnership between dbt Labs, Atlan, and different trade leaders, organizations will be capable to profit from unprecedented consistency and precision of their key metrics.

Margaret Francis, Chief Product Officer at dbt Labs

Right here is how joint clients profit from Atlan and dbt Labs’ partnership:

  • 360° metric profiles: Similar to a knowledge asset, each dbt metric is now a first-class citizen with a full profile in Atlan. Information groups can discover and confirm metrics, assign house owners, personalize entry, connect documentation, observe modifications, discover downstream belongings, and extra.
  • Metrics querying: With our Visible Question Builder, non-technical information customers can now question dbt metrics — democratizing information and lowering dependencies on analytical and information engineers.
  • Finish-to-end, column-level information lineage: We use automated SQL parsing to create end-to-end, column-level lineage for all dbt transformations. This reveals how every dbt mannequin impacts not simply upstream warehouses but additionally downstream BI studies and dashboards.
  • Activating metric context into BI: With our Chrome extension, dbt metadata is now accessible in downstream BI instruments like Looker and Tableau.
Atlan's Chrome extension makes context around a dbt Revenue metric available in a financial Tableau dashboard
Atlan’s Chrome extension brings dbt metadata to the locations the place you’re employed every single day. For those who’re in a BI dashboard, no want to modify instruments and go looking for context in dbt.

This new partnership and integration comes on the heels of our main launch, that includes a whole redesign and slate of brand-new options, integrations, and partnerships. We have been additionally just lately named a Chief in The Forrester Wave™: Enterprise Information Catalogs for DataOps, Q2 2022.

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