Recently, dbt Labs launched the dbt Semantic Layer — allowing data professionals to define metrics in dbt projects, and query them from any integrated analytics tool.
Collibra is proud to be a dbt Metrics Ready Launch Partner. Metrics Ready integrations facilitate building, discovery, and collaboration on dbt metric definitions. You can download and get documentation for the API integration at the Collibra Marketplace now.
The dbt Semantic Layer powers organizations by centrally defining key business metrics like ‘revenue,’ ‘customer count,’ or ‘churn rate’ in dbt, and query them in downstream analytics tools — so every business professional can feel confident they’re working from the same assumptions as their colleagues, regardless of their data tooling. If a metric definition is updated in dbt, it is seamlessly updated everywhere, ensuring consistency throughout the business.
As Callum McCann, Senior Developer Experience Advocate at dbt Labs wrote in Understanding the components of the dbt Semantic Layer: “the dbt Semantic Layer is a collection of components combined to create a single experience through which business users can query data in the context of the metric that is most familiar to them”.
Collibra integration makes dbt semantic layer better
Dbt Metrics Ready integrations such as Collibra’s facilitate building, discovery, and reliability of dbt metric definitions. Collibra’s integration allows users to get visibility on metadata and lineage for dbt metrics inside Collibra.
Like Collibra, dbt Labs participates in an ecosystem of interoperable tools which represent a best-of-breed approach to building a modern analytics practice. But with each new tool added, the entire infrastructure becomes a little bit more unstable and a patchwork of inconsistent, fragmented, and siloed data, definitions, metrics, etc. across the different systems.
To fix this, we’ve worked on a dbt Metrics Ready integration around shared definitions for core business entities, relationships, and metrics. With this integration, Collibra gives customers a single location to find, understand and create a shared language around data, define the terminology, rules and regulations, and deliver trusted data to the business.
Leverage a single, scalable data catalog and governance solution that delivers all of the capabilities you need to take back control of your data landscape, improve the efficiency of your people and processes, and reduce your data and compliance risks:
Quickly find, understand, and govern your data
dbt Semantic Layer leverages a single platform to deliver full visibility into business-critical data assets, including metrics, reports, APIs, models, data products and technology assets, with full business context attached.
Drive a common language around data to speed decision making
Now, you can build a business glossary to ensure clarity and consistency of critical business definitions and metrics and create a shared language for data within your organisation so everyone has a single source of truth.
Mobilize your workforce to encourage collaboration
With dbt, you can enable data stewards to join forces with subject matter experts and data owners through automated workflows, role-based dashboards, and interactive views, as well as automate processes with out-of-the-box and customizable workflows for common governance and stewardship processes.
Collibra Data Intelligence Cloud accelerates data modernization by allowing more people across your organization to find, understand, trust and access the right data at the right time. See Collibra Data Governance in action here.
Looking to the future
Recently, we released an API integration that registers models, metrics, data quality rules (soon) and all table and column technical lineage dependencies. We’ll soon be registering all available resource metadata found in the resource meta field.
We’re also working to bring the context and knowledge stored in its platform as close to the dbt user as possible.
Through it all, our mission is to deliver better quality insights (i.e. ownership, data classifications, data categories, data access policies, quality scores and warnings, tags, etc) while also making those insights simpler to find and faster to access — without the need to leave either system of engagement.