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Atlan Turns into dbt Semantic Layer Launch Associate and Publicizes 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 various information groups.

As we speak we’re excited to announce our partnership with dbt Labs, the pioneer in analytics engineering. As a part of this, joint clients can 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 price” in dbt, and question them in downstream analytics instruments. This permits 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 selection. If a metric definition is up to date in dbt, it’s seamlessly up to date in all places, guaranteeing 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 are actually part of column-level lineage, spanning from supply techniques and information storage to transformation and BI.

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

We’re excited to associate with dbt Labs to make metrics a first-class citizen for information groups.

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

Now, with Atlan and dbt, various information folks can minimize via 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 folks work each day.

With this, when questions come up about firm information, information groups can rapidly discover the proper metric, backtrack via adjustments by way of model management, assess precisely what modified at each layer (i.e. the info, definition, and operational layers), and hint how downstream property had been affected. This highly effective affect and root trigger evaluation lastly provides 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 provides 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 business leaders, organizations will have the ability 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: Identical 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 homeowners, personalize entry, connect documentation, monitor adjustments, discover downstream property, 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 exhibits how every dbt mannequin impacts not simply upstream warehouses but additionally downstream BI stories 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 each day. In case you’re in a BI dashboard, no want to change instruments and go trying to find context in dbt.

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

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