At Concord, we see firsthand how enterprises are racing to unlock real value from AI and data-driven applications across the entire data lifecycle. What’s become clear is that a strong, trusted data foundation is essential to make this happen. That’s exactly the message Snowflake emphasized at their Summit this year.
Across four packed days and three visionary keynotes, we saw a focus on helping organizations turn raw data into action, infuse AI into every layer of the business, and do it all with governance, flexibility, and trust. As longtime Snowflake partners, we left energized by the direction and the potential for our clients to work smarter, faster, and more efficiently.
Here are some of the standout announcements and what they mean for your business.
The theme of centralization ran strong, particularly for data engineers and analytics engineers juggling fragmented workflows. One of the most exciting changes? dbt projects now run natively within Snowflake (public preview), eliminating the need to bounce between platforms. This streamlines the analytics engineering process and supports the kind of full-stack, end-to-end workflow we’ve long championed at Concord.
The introduction of Openflow, Snowflake’s fully managed data movement service powered by Apache NiFi, is another big leap. With support for structured, unstructured, and streaming data, Openflow positions Snowflake to reduce reliance on third-party tools. That said, with over 500 connectors, we expect a healthy ecosystem will remain. But for supported sources, Openflow could mean simpler architectures and fewer vendors to manage.
Also noteworthy: Snowpipe pricing is shifting from file-plus-compute to a volume-based model, with an average 50% cost reduction. This is a welcome change that makes real-time ingestion more predictable and accessible, especially for teams scaling operations.
If there was any hesitation about whether it’s time to adopt AI, Snowflake and its keynote guests, especially OpenAI CEO Sam Altman, cleared that up. Altman put it bluntly: “Just do it.” He warned that organizations waiting on a “better model” risk falling behind as others build momentum.
Snowflake’s response? A full-stack AI-native platform that makes AI approachable and powerful at once.
This is where AI meets governance and usability, a combination that’s not only innovative but necessary for enterprise adoption.
While the vision for Snowflake Intelligence is groundbreaking, it’s important to set realistic expectations. Based on the rollout cadence of prior launches like Document AI and Arctic, we anticipate general availability may be 12–24 months away across all regions. Pricing will also likely reflect the advanced capabilities and computational load.
That said, forward-looking organizations can act now by investing in semantic model development, data cataloging, and AI-readiness, which lays the foundation for full adoption when the tools hit GA.
From enhanced Apache Iceberg support to Terraform provider GA and Python 3.9 in Notebooks, Snowflake continues to champion an open, developer-friendly ecosystem. This means teams can move faster without being locked into rigid systems.
With the Horizon Catalog enhancements, like lineage visualization, auto-classification, and metadata Copilot, Snowflake also strengthens data governance across hybrid and multi-cloud environments. These features ensure that as teams accelerate, they do so with security, traceability, and compliance in place.
And with the deprecation of password-only logins in favor of stronger authentication methods, Snowflake is doubling down on enterprise-grade security.
Snowflake isn’t just enabling internal innovation, it’s empowering developers and partners to build AI-native apps directly in the Snowflake Marketplace using agentic frameworks. With Cortex Knowledge Extensions, these apps can tap into real-time external content while protecting IP and maintaining attribution.
Meanwhile, Semantic Model sharing opens the door for secure, governed collaboration across teams and organizations, an exciting step toward truly federated AI.
As Snowflake co-founder Benoît Dageville put it: “We want to give you flexibility, but not overwhelm you.” The innovations announced this year show Snowflake delivering on that promise by offering simplicity without sacrificing power, and speed without compromising trust.
At Concord, we believe the winners in this next chapter of enterprise data will be those who move decisively and bring together AI, governance, and modern data engineering practices on a unified foundation.
We’re excited to help clients activate these innovations. Not just by adopting new tools, but by aligning people, processes, and strategy to drive meaningful impact.
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