Snowflake Summit 2025: AI, Data Trust, and Metadata in Action

At this year’s Snowflake Summit in San Francisco, thousands of data leaders gathered to explore how AI, cloud innovation, and modern data strategies are reshaping the enterprise. Alation was there, spotlighting real-world stories of data transformation from customers Boston Children’s Hospital, O’Reilly Auto Parts, Swire Coca-Cola, and Fortune Brands Innovations.

In this blog, we’ll recap key learnings from these customer spotlights. But first, let’s set the stage—with the keynote that set the tone for the week.

Keynote recap: “Just do it”—AI in prod starts now

The 2025 Snowflake Summit opened with a powerful message from OpenAI CEO Sam Altman and Snowflake CEO Sridhar Ramaswamy: The time for experimenting with AI is over. The time to build is now.

In a candid fireside chat, Altman and Ramaswamy made the case for accelerating AI adoption—not in five years, but today. “The companies that have the quickest iteration speed and make the cost of making mistakes low—those are the ones that win,” said Altman. Ramaswamy echoed the urgency: “What we assumed about how things work just doesn’t hold anymore.”

Their message resonated with one of the Summit’s biggest themes: turning complexity into clarity. As AI agents evolve from experimental sidekicks to productive team members, enterprise leaders must design systems that are not only powerful but trusted, governed, and simple to use.

That clarity starts with data. “There is no AI strategy without a data strategy,” Ramaswamy emphasized. This sentiment was echoed throughout the Summit and through the stories Alation’s customers shared on stage.

From Boston Children’s Hospital relaunching data governance as an enabler rather than a blocker, to Swire Coca-Cola building trust in data through a product-based model, one theme was clear: the future of AI-driven enterprise success depends on making data usable, discoverable, and governed from the start.

With the stage set, let’s dive into how Alation customers are putting these principles into action. 

How Boston Children’s Hospital rebooted data governance as enabler

At Boston Children’s Hospital (BCH), data isn’t just an operational asset—it’s a strategic driver of clinical excellence, research advancement, and operational efficiency. With growing complexity across systems, teams, and metrics, BCH needed a new approach to unlock the full potential of its sensitive healthcare data.

“We have a high demand for data,” said Jared Hawkins, Sr. Director of Enterprise Data, Analytics & Reporting. “People want to leverage it to improve clinical, operational, and financial workloads.” However, without governance, inconsistency and inefficiency creep in.

Turning governance from a “dirty word” into a strategic enabler

Before the reboot, data governance had become a barrier rather than a bridge. “Governance became a dirty word,” Hawkins admitted. “It was viewed as stopping people from innovating and accelerating their work.”

Recognizing this, BCH launched “Governance 2.0”—a total reset in both mindset and execution. The goal: rebuild governance as an enabler, not a blocker. This meant repositioning governance to focus on collaboration, transparency, standards, and protection.

To design this new model, BCH partnered with Archetype Consulting. As Oliver Courtney, Head of Digital Advisory at Archetype, put it, “We framed our strategy around unlocking the full potential of data. Governance was repositioned as an enabler, not an obstacle.”

Listening first: A governance reboot built on leadership input

The team began by interviewing senior leaders across the hospital to understand their data challenges, needs, and frustrations. These insights helped shape a clear mandate and set of initiatives for the new governance model.

“We created a mandate by asking leaders, ‘What do you need from data?’” said Courtney. “This helped us shape a collaborative strategy rooted in the real needs of the business.”

The result was a renewed operating model supported by an executive-level steering committee, a new data governance council, and role-specific working groups to execute key priorities.

Building the operating model: Roles, charters, and accountability

Governance 2.0 at BCH was built with clarity. Roles were defined from the perspective of the people in them, including terms of reference and expected outcomes for everyone—from the data governance manager to data stewards.

“The key to success,” noted Courtney, “was giving people ownership and clear expectations. That builds accountability.”

The program also included:

• A data governance council chaired by Hawkins to set direction

• Working groups for analysts, technical experts, and legal/compliance stakeholders

• A prioritization process that empowered leaders to decide what initiatives mattered most

Anchoring governance in real-world impact

Rather than getting lost in theory, the BCH team focused on practical wins.

“We prioritized data quality—technical and clinical validation,” said Hawkins. “We validated definitions, traced errors in workflows, and built trust in the process.”

They also tackled classification policies and role-based access controls, ensuring sensitive data remained secure yet usable. Meanwhile, Alation’s data catalog became the linchpin for discovery, transparency, and collaboration.

“Business users are now entering definitions and actively using the catalog,” Hawkins shared. “That’s a real sign of success.”

Governance as a foundation for AI readiness

AI is a strategic priority at BCH—but Hawkins was clear: “AI needs a strong data foundation to succeed.” Governance provides that foundation, enabling trustworthy, consistent, and discoverable data that AI models can rely on.

By treating governance as a prerequisite for AI, the Governance 2.0 program gained organizational momentum. Early AI wins became proof points, reinforcing why data governance matters and reframing its role as a gateway to innovation.

Lessons learned: Secure buy-in and focus on outcomes

Both Hawkins and Courtney emphasized two core lessons learned from this process:

Secure top-down and cross-functional buy-in. “Link governance to what leadership cares about—OKRs, patient outcomes, research,” said Hawkins. “And make it a team sport, not an IT initiative.”

Focus on outcomes, not activity. “We moved from tracking data loads to measuring impact,” Courtney explained. “Our roadmap links objectives to real actions, with clear accountability.”

Governance as infrastructure, not interference

Courtney summed up the team’s philosophy by comparing governance to traffic rules. “Governance is like the road system—it doesn’t drive the car, but it enables you to go where you want, safely and efficiently.”

At Boston Children’s, governance isn’t about control—it’s about enabling innovation with confidence. With clear roles, collaborative frameworks, and strategic vision, the hospital is unlocking the full potential of its data—one definition, one workflow, and one AI model at a time.

How Swire Coca-Cola delivers trust with data products

Swire Coca-Cola is the largest independent bottler in the U.S. West. Today, it serves over 30 million customers and distributes more than 250 products across 13 states. But behind every can of Coke is a vast and complex data ecosystem. 

Bharathi Rajan, VP of Enterprise Data and Insights, shared how Swire moved from data chaos to clarity by adopting a data product approach—supported by a new mindset, stronger data governance, and a key partnership with Alation.

Building a foundation for trustworthy data

“If my end users, my stakeholders, don’t trust the data, I’m not doing a great job,” Rajan said—and that belief became the foundation of Swire’s transformation.

When she joined the company three years ago, Rajan inherited a fragmented landscape. “There was data,” she recalled, “but no foundational model to support enterprise-wide use… there were data trust issues.”

To rebuild trust, her team began by standardizing definitions and consolidating key metrics across departments. A prime example was the OTIF (on-time, in-full) manufacturing metric. “Everyone had their own way of calculating it,” Rajan explained, leading to confusion and misalignment. “We brought all stakeholders together and created a single, standard calculation.”

This alignment didn’t just improve accuracy—it became a catalyst for cultural change. Trust in the data grew, enabling better decisions across the business.

Shifting from data sets to data products

“At the end of the day, I want to build trust in the data,” said Rajan. “A data product is one of the ways to build that trust.”

Instead of creating individual data sets for every report request, Swire adopted a product-based approach. Certified data products became standardized, reusable, and easier for teams to trust. “They know they’re getting certified data,” Rajan said, “and it’s a product that can be used in multiple different ways.”

To reinforce this mindset, Swire introduced a custom metric called DOTIF—Data On-Time In-Full—focused on delivering high-quality data at the right time, in the right format.

Accelerating adoption with Alation

To support their new model, Swire turned to Alation. “It was about more than features,” said Rajan. “We wanted a partner that understood our strategy and could grow with us.”

Branding played a key role in driving adoption. Swire named its Alation-powered knowledge hub “CHILL”—short for Cona Hub for Information, Lineage, and Logging. This central platform offered users a clear path to find, understand, and trust the data they needed.

Gordon Bonzo, Manager of Enterprise Master Data at Swire Coca-Cola, emphasized how CHILL was embedded into daily workflows. “We made Alation part of our CI/CD pipeline,” Bonzo said. “Documentation and certification are now built into the process—not an extra governance checklist.”

The impact: A flywheel of trust and productivity

The results speak for themselves. “We no longer spend hours tracking down issues,” Rajan said. “Stakeholders verify before escalating. They trust the data.”

And the feedback from the business proves it. “One user told me, ‘Alation is the best thing you guys have done,’” Rajan shared. “That’s how we know we’re on the right path.”

Swire’s journey shows how trust is the cornerstone of modern data success. By treating data as a product and embedding governance into the fabric of daily work, Swire empowered its teams with confidence, accelerated decision-making, and unlocked real business value—powered by Alation.

How O’Reilly Auto Parts drives data clarity with Alation and Snowflake

Next, Dwayne Foresee, part of the data strategy team at O’Reilly Auto Parts, took the stage to share how the company overhauled its data environment—boosting trust, reducing cloud costs, and laying the foundation for AI innovation. The key? Treating metadata not as a byproduct, but as a roadmap, powered by Alation.

From data hoarding to data stewardship

With 6,300+ stores and 93,000 employees, O’Reilly operates in a mission-critical industry. When the company’s legacy data ecosystem reached end-of-life in 2023, it wasn’t just time to migrate that data to the cloud—it was time to rethink.

“We didn’t want to forklift a garage full of junk into a bigger garage,” Foresee said. Instead, the team paused to catalog, classify, and assign ownership to its sprawling data assets before moving anything into Snowflake. “Alation needed to be the starting point,” Foresee explained. “We implemented Alation before we even stood up our Snowflake environment.”

Building trust through governance

A central part of O’Reilly’s modernization strategy is aligning business teams with data governance. Every asset moving into Snowflake now requires business sign-off—complete with proper descriptions, classifications, and steward assignments in Alation.

To help business users engage confidently, Foresee’s team created standardized discovery workflows in Alation. Filters and saved searches help stewards focus only on the tables relevant to them. “It’s a nerve-racking thing to become a data steward,” Foresee said. “Alation helps guide them step by step.”

This structure has dramatically improved trust and visibility across the business. “People were using reports and queries that were 10 years old and assuming they were accurate,” Foresee said. “Now we’re asking: Do you know if this data is verified? Up to date? Compliant?”

Metadata that reduces waste and powers insight

By ingesting query logs from tools like Domo and DB2, Alation gave O’Reilly visibility into which queries were most used—and which were wasting resources. “Alation shows us which queries have been run 30,000+ times,” Foresee said. “That’s incredibly useful for understanding what’s working and what isn’t.”

This insight doesn’t just improve decision-making—it drives operational efficiency. By identifying redundant or inefficient queries, O’Reilly can reduce compute usage and cloud costs in Snowflake.

Laying the groundwork for AI and agents

O’Reilly’s long-term goal? Enable AI-powered agents and automation. But Foresee was clear: that future depends on trustworthy, well-governed data. “If you want agents making decisions, you’d better know where your trusted queries are,” he said. “You need lineage, ownership, and validation. Alation makes that possible.”

Why Alation? It’s the partnership

Foresee closed with a nod to the selection process. “We evaluated several platforms over seven months,” he said. “What made Alation stand out was the partnership. We didn’t want a vendor—we wanted someone who’d build with us. Alation committed to our goals, including building a Domo connector when others wouldn’t.”

How Fortune Brands unified data with ALTR and Alation

As part of a major data modernization effort, Fortune Brands Innovations (FBIN) consolidated brand-level data into Snowflake. But with data scattered across disparate stacks and security concerns at the forefront, the company needed more than just a central data warehouse—it needed secure, governed access to data across its enterprise.

In a fascinating session, Laura Malins, VP of Product at ALTR, detailed how Fortune Brands achieved this by integrating ALTR’s data security platform with Alation’s data catalog—bridging the gap between governance and access control.

The data challenge: Fragmentation and risk

Fortune Brands owns well-known consumer brands like Moen, Master Lock, and Therma-Tru. Each had its own data stack, tools, and governance models. “Reporting was fragmented, delayed, and heavily manual,” said Malins.

Beyond data consolidation, FBIN needed to ensure that corporate users couldn’t access brand-level sensitive customer data—demanding precise, role-based access controls in Snowflake.

Empowering data stewards with Alation and ALTR

To meet these requirements, FBIN deployed a joint Alation-ALTR solution. “Alation was the brain, ALTR was the muscle,” Malins explained. Alation’s SDK and ALTR’s APIs created a seamless experience where business users—especially data stewards—could identify sensitive data, tag it, and manage access without relying on engineers.

ALTR’s native Snowflake app scanned data for sensitive attributes like emails, names, and credit card numbers. These classifications flowed into Alation, where stewards could apply Snowflake object tags. “Tagging is critical,” said Malins. “Without it, every policy must be written per column—it’s unscalable.”

Enabling self-service and real-time compliance

Once tagged, ALTR’s no-code UI allowed business users to define and enforce data access policies. For instance, users with a “public” role saw masked values, while admins saw full details. Policies could even trigger alerts or block suspicious behavior.

“We wanted to take work off the engineers’ plates,” said Malins. “Now stewards can manage access confidently, directly in the tools they use.”

Beyond control, ALTR delivers real-time auditing, alerting, and blocking—essential for compliance. Fortune Brands can now monitor who accessed what data, when, and how, across Snowflake and other cloud warehouses.

“The ALTR-Alation integration gave FBIN not just classification and tagging,” Malins said, “but a complete security model that scales.”

A model for modern data governance

By integrating cataloging and security, Fortune Brands achieved what many enterprises struggle to do: deliver secure, self-service data access at scale.

“Data stewards don’t just understand the data—they now control access to it,” said Malins. “That’s a huge shift in governance maturity.”

Conclusion: The metadata engine powering AI readiness

Across industries—from healthcare to manufacturing to retail—Alation customers are proving that trusted, governed data is the bedrock of AI success. Whether it’s enabling clinicians, empowering supply chain leaders, or modernizing self-service analytics, each story highlights the same truth:

• Data must be findable, usable, and trusted

• Governance must be built-in, not bolted on

• Metadata is the fuel that drives operational agility and AI adoption

Alation is more than a catalog. It’s a metadata-powered platform designed to help enterprises govern with confidence, deliver value through data products, and prepare for the next generation of AI.

Because when your data is governed, your business is ready—and your AI is, too.

Learn more about our vision for data for AI in the enterprise:

• See the Alation Agentic Platform, Documentation Agent, and Alation Data Quality product pages

• Explore the Data Products Marketplace

• Read the press releases: Alation Agentic Platform, Data Products Marketplace, Data Quality

• Explore our professional services offering, the Data Products Playbook