Domo, a provider of AI and Data Products platforms, has announced its membership in the Open Semantic Interchange (OSI), an open-source initiative led by Snowflake aimed at creating a universal specification for standardizing fragmented data definitions.
The OSI initiative seeks to enable companies to align on shared, vendor-neutral semantics, ensuring consistent metrics and definitions across various data applications, including dashboards, notebooks, and machine learning models. This collaborative effort is supported by Snowflake, the AI Data Cloud company, alongside ecosystem partners like Domo from sectors such as AI, business intelligence, data governance, data engineering, financial services, and manufacturing.
The primary goal of OSI is to accelerate data interoperability between platforms, streamline data operations, and reduce complexity. This standardization is crucial for organizations looking to fuel AI innovation with consistent and trusted data.
Ben Schein, Chief Analytics Officer at Domo, commented on the initiative, stating, “This is about eliminating the chaos of conflicting metrics. OSI will help our customers go from fragmented data definitions to broadly understood insights, a critical step to ensuring their data is AI-ready and able to power agents and apps that drive real business outcomes.”
As a contributing member of OSI, Domo is involved in building a transparent and community-driven standard for semantic model sharing, which aims to ensure that business metrics and definitions remain consistent and interoperable across the ecosystem.
Josh Klahr, Director of Analytics Product Management at Snowflake, emphasized the importance of the collaboration, saying, “Unlocking the full potential of data and AI requires a common foundation, and the Open Semantic Interchange is a critical step in building that bedrock. Our collaboration with partners like Domo establishes a unified, vendor-neutral standard for semantic data, promoting clarity and consistency across the entire ecosystem. This initiative is essential for simplifying data operations, fostering innovation, and preparing organizations to build the next generation of AI applications.”
OSI aims to redefine how data and AI tools interact by establishing a universal standard developed by the community. This collective approach is designed to simplify data operations, unlock new possibilities for innovation, and provide organizations with the flexibility and efficiency needed to develop a future-ready data infrastructure.
