At the beginning of June, Snowflake Summit 2025 brought together thousands of data and AI professionals in San Francisco to showcase the future of enterprise data. From the moment the first keynote began, it was clear: this year’s event wasn’t just about incremental updates — Snowflake is making bold moves.
The demos were impressive. The keynotes were visionary. And the message behind the product roadmap was loud and clear: AI-first, faster pipelines, lower costs, and more control.
Snowflake made many multiple announcements that were extremely interesting both for me personally, and C&F as a company that helps clients use their data more effectively. The list was really long and included:
- Adaptive Compute for performance
- Major Snowpipe cost cuts
- Snowpipe Streaming upgrades
- Horizon Catalog (GA)
- Openflow
- SQL-based Semantic Views
- dbt Projects integration
- Cortex AISQL
- Snowflake Postgres
But while those announcements are impressive and their potential is sky high, many companies should pause for a reality check. As exciting as these new features are, they won’t solve foundational issues on their own.
We’ve seen it before: organizations rush to adopt the latest tools, eager to stay ahead. But without strong data fundamentals: clear governance, defined ownership, and consistent standards, even the most advanced capabilities can become difficult to manage, and the promised value fails to materialize. It all collapses under its own weight.
The Flood of Innovation
This year’s announcements made one thing clear: Snowflake is no longer “just a data warehouse.” It’s evolving into a fully-fledged data operating system. A platform that empowers every kind of user:
- AI in the hands of analysts.
- Streaming in the hands of engineers.
- Postgres in the hands of developers.
Everything’s faster, more open, and more accessible than ever. But that momentum can only take you so far.
If your data catalog is messy, your pipeline logic lives in tribal knowledge, and your team doesn’t trust the metrics they rely on, then there’s no actual value being delivered. All that speed and incredible tools just get you to the wrong answer faster.
From Shiny Features to Stable Foundations
The smartest, most forward-thinking data teams at Summit weren’t chasing features. Instead, they were focused on fundamentals. They were asking:
- Do we have a clear data model?
- Who owns quality and access across domains?
- How can we scale governance with this new wave of flexibility?
This is where tools like Horizon Catalog, Semantic Views, and dbt Projects can show their true value, but only when they’re paired with a strong governance strategy. After all, AI Agents and Inline Copilot are only as smart as the data you feed them.
What Smart Teams Will Do Next
The key takeaway from this year’s Summit isn’t just about the technology — it’s about the strategy behind it. Smart teams know that adopting new features without foundational clarity is a recipe for future rework. They’re taking a thoughtful approach:
- Govern first. Build second
- Adopt Cortex only when your data is trusted.
- Deploy dbt Projects only when ownership is clear.
- Lean into Horizon only if your catalog reflects reality.
The value is real, but so are the risks of scaling without proper foundations. This Summit proved Snowflake is ready for the future. The question is — are you? And the answer depends not on how many features you adopt, but on how strong your data foundation really is.
At the Summit, nearly every session circled back to AI. Use natural language to query data. Automate pipeline decisions. Bring intelligence into your warehouse. Snowflake’s vision is powerful, but without structure, it can produce risks. AI built on poor data leads to bad decisions. Even worse, it builds false confidence. That’s how small mistakes turn into enterprise-wide failures.
And as companies double down on AI, governance becomes non-negotiable. Before investing in new tools, ask yourself: will it really help me solve my challenges, or do I just need smarter control of the tools I already have?
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