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dbt Labs Commits to Open Semantic Interchange by Open Sourcing MetricFlow

At its annual conference, Coalesce 2025, dbt Labs made headlines by announcing the open-sourcing of MetricFlow under the Apache 2.0 license. This initiative is a significant stride toward enhancing trustworthy AI, an area where dbt Labs has established itself as a leader in AI-ready structured data standards. Moreover, this release aligns closely with the company's commitment to the Open Semantic Interchange (OSI) initiative, spearheaded by industry heavyweights such as Snowflake, Salesforce, and Sigma. Together, they aim to establish vendor-neutral standards for the semantic exchange of data across various analytics and AI platforms.

The Need for Standardized Metrics

In the race to deploy AI, organizations often encounter issues related to inconsistent metrics and fragmented definitions. This turmoil hampers trust and can slow down the adoption of AI technologies. Hence, there is a pressing demand for a unified standard that all tools and agents can trust. MetricFlow serves as the foundational engine that compiles metric definitions into code, ensuring that the calculations it performs are reliable and easily understandable—a stark contrast to methods like text-to-SQL.

Governance in AI-Ready Data

Following the acquisition of Transform in 2023, MetricFlow has enabled the dbt Semantic Layer, drawing upon configurations from semantic models and metric definitions to execute SQL in data platforms. By open-sourcing MetricFlow, dbt Labs is opening up a world of possibilities for developers and data analysts alike. The new Apache 2.0 license invites the community to utilize a transparent, extensible engine, bolstering the use of trusted metric definitions for governed conversational analytics. The goal is clear: to provide consistent results irrespective of the tools and clouds involved, making it easier for organizations to scale their analytics capabilities.

A Transition Rooted in Open Source DNA

According to Ryan Segar, the Chief Product Officer of dbt Labs, the transition to an open-source model for MetricFlow will unlock unprecedented opportunities for data professionals. Analysts overwhelmingly agree that their demand for more efficient tools is critical to meeting growing business needs. The open-sourcing of MetricFlow mitigates the need for constant rework, reigniting trust in data among organizations across the board.

Collaborative Efforts for Semantic Standardization

dbt Labs' commitment to the OSI initiative highlights the pressing need to standardize data definitions, which can be costly if left unchecked. Josh Klahr, Director of Analytics Product Management at Snowflake, expressed that fragmented data definitions pose significant obstacles to AI adoption. He believes that MetricFlow is set to play a vital role in creating a shared set of analytic metadata, essential for accelerating the journey toward trustworthy data utilization.

Furthermore, experts like Rob Vicker, Data Analytics Architecture Director at EMS Insurance, stress that implementing MetricFlow is paramount for creating a unified source of truth. With many analytic tools interpreting metrics differently, the open-source nature of MetricFlow ensures that all tools provide consistent metrics consumption—saving time for analysts while simplifying audits and offering users the options they desire without the hassle of ongoing code updates.

A New Era for Data Practitioners

As organizations prepare for a world increasingly driven by AI, the significance of standardized metrics cannot be overstated. By providing the flexibility needed for adapting to different analytical approaches, open-source MetricFlow has the potential to transform how businesses consume data. Since its inception in 2016, dbt Labs has been on a mission to empower data practitioners. With the open-sourcing of MetricFlow, the company is not only championing a comprehensive approach to data governance but also reinforcing its commitment to helping organizations scale their analytics in this electronic age.

To learn more about dbt Labs and the open-sourcing of MetricFlow, visit their website at getdbt.com.