A semantic model centralizes business logic so every surface, BI and AI, uses the same meaning. Snowflake’s Open Semantic Interchange (OSI) is an ecosystem initiative to make those semantics portable across tools. Select Star is excited to be a launch partner supporting this mission to improve interoperability and accelerate outcomes for joint customers.
Why Most Teams Need a Semantic Layer
A semantic layer turns scattered logic (copied SQL in dashboards, conflicting metric definitions across BI tools, and transformation code spread across dbt/ETL pipelines) into shared understanding. In practice, that looks like a few concrete wins. Your teams get consistent answers across tools because each metric or dimension has one governed definition. You do less rework and fewer handoffs because business logic lives centrally instead of being copied across dashboards. You gain explainability and trust with end‑to‑end lineage and clear ownership, which speeds audits and incident triage. And you get portability for the future as definitions move between tools without lock‑in. Most importantly, the data context (owners, glossary terms, policies, and usage) travels with the definition so semantics are actually operational.
Shinji Kim, founder and CEO of Select Star, explains why semantic layers matter: “AI doesn’t just need data; it needs understanding. A semantic model provides that by defining shared metrics, terms, and relationships across your data. Without it, you risk inconsistent answers and a lack of clarity around how results are produced. It’s the context that grounds AI in how your business actually works.”
Snowflake and Other Industry Leaders Partner on an Open, Interoperable Future: What OSI Means for Data Leaders
Open Semantic Interchange (OSI) is an open source initiative led by Snowflake and ecosystem partners to create a universal, vendor‑neutral semantic model specification. Its goal is to standardize fragmented data definitions and make semantic metadata portable across tools and platforms. By enabling the exchange of semantics in a standard, open format, OSI improves interoperability and helps enterprises deliver consistent metrics and definitions across dashboards, notebooks, and machine learning models.
“The Open Semantic Interchange is a critical step toward unlocking a new era of interoperability across the data and AI ecosystem,” said Snowflake spokesperson. “By working with partners like Select Star, this initiative ensures a common, standardized understanding of semantic data across tools. This will enhance interoperability and vendor neutrality, providing organizations with greater flexibility and efficiency in building their data infrastructure, and simplifying data operations.”
In today’s mixed‑tool reality (multiple BI platforms, notebooks, and emerging AI apps), even “settled” KPIs drift as teams copy logic between systems or migrate tools. OSI provides a common way to package and exchange semantic metadata so they remain consistent wherever they are consumed. As a launch partner, Select Star is contributing real‑world feedback and use cases to help the initiative focus on day‑one outcomes such as KPI consistency, safer migrations, and AI readiness, without forcing a new modeling tool or vendor lock‑in.
Why data leaders should care
- Consistent answers across BI and AI. Shared semantic metadata reduces drift so dashboards and assistants agree.
- Lower migration and modernization cost. Move definitions forward when consolidating or trialing new tools without re‑modeling from scratch.
- Faster time to adoption. Standardized interchange shortens the path from pilot to production for new analytics and AI surfaces.
- Explainability on day one. When semantics travels with lineage, owners, and definitions, audits and incident triage move faster.
- Ecosystem momentum. Vendors and partners align on a common way to interchange semantic metadata, reducing one‑off integrations.
Learn more about the Open Semantic Interchange on Snowflake’s blog.
How Select Star Delivers an Interoperable Semantic Layer for Snowflake
Select Star is a metadata context platform that helps data teams turn the BI they already trust into an interoperable semantic layer for Snowflake. We reverse engineer dashboards and SQL from Looker, Tableau, Power BI, and other BI tools to generate governed metric and dimension definitions in days, not months. Each definition carries ownership, glossary terms, policies, and end-to-end lineage so answers are explainable and auditable. We help data teams reconcile duplicate KPIs, establish stewardship, and align semantics with Snowflake’s Open Semantic Interchange so they can travel across tools as OSI matures.
How Select Star Autogenerates Semantic Models
- Connect. You connect Select Star to your BI tool (Looker, Tableau, Power BI).
- Scan. Select Star automatically scans dashboards, worksheets, and metrics.
- Reverse-engineer. Select Star generates a semantic model with metric definitions and source lineage.
- Govern and extend. You can review, govern, and extend the yaml file.
- Publish. Make the semantic models available to Snowflake Cortex Analyst, ChatGPT, Claude, Cursor, or any AI tools right away.
Explore more on semantic models with our post on self-service data analytics and Snowflake Cortex Analyst.
Get Snowflake‑Ready Semantic Models from the BI You Already Have
Teams like Faire, Datasembly, and Opendoor show what is possible when you leverage rich data context — data lineage, usage, ownership, and definitions — to ground analytics and AI. Faire achieved ~70% pipeline cost reduction and ~80% fewer debugging hours on Snowflake by using lineage and usage insights to standardize work. Datasembly completes projects 90%+ faster and reports $30k+ annual Snowflake cost savings through context‑driven consolidation. Opendoor reports faster triage and self‑serve gains, along with major analytics cost reductions, by making governed metrics discoverable and trusted.
Ready to see this on your data without rebuilding from scratch? Connect with our team and see your dashboards reverse‑engineered into a governed semantic model, complete with lineage and OSI‑aligned interoperability, so your teams get consistent, explainable answers in days, not months.
Join the Open Semantic Interchange (OSI) Initiative
Fragmented definitions are one of the biggest barriers to trustworthy AI. OSI brings industry leaders together around an open, vendor-neutral specification so definitions can travel across tools without drift. If you want to help shape a more open and connected data future, start with Snowflake’s official OSI announcement here.
