Data Mesh is more than an architecture – it’s a promise of a new way to collaborate. In this session, we explore what it takes to create a living data ecosystem that goes beyond Data Mesh, combining tools, innovation, processes with accountability@ENBW Trading. Inspired by the dynamics of a Tour de France team, we’ll look at the success factors that turn structures into real movement – and ask the question: Who will shape the future of data work, and how?

This session puts the spotlight on STADA’s journey in transforming data accessibility for better decision-making. As a trusted Snowflake customer, STADA has prioritized consistent and reliable data by centralizing its commercial and supply information on Snowflake’s platform. With EPAM’s support and innovations enabled by Cortex technology, STADA has empowered its employees with intuitive tools to navigate complex data with ease. Join us to hear how STADA is driving efficiency and unlocking the full potential of its data.

The retail and consumer goods industries are undergoing significant transformation, driven by shifting consumer behaviors, global economic changes, supply chain disruptions and, most importantly, rapid technological innovation. This session is designed for business and technology leaders in RCG, offering them insights and strategies needed to navigate and thrive in this evolving landscape. Learn from the transformational experience of the leading global consumer goods company, Snowflake industry experts and key partners as they explore how data and AI technologies are shaping the industries' future.

In this session, We will enable CDAO's Enterprise Data Strategy by exploring the full lifecycle from the concept of data products—packaged, readily consumable data assets—to their distribution through Snowflake's internal marketplace.

We will drive home 5 key points within this data product lifecycle: 1. Simplified data access for business users 2. Improved data discoverability and understanding 3. Increased data utilization and adoption 4. Accelerated time to insight 5. Metrics & Considerations

Modern data engineering leverages Python to build robust, scalable, end-to-end workflows. In this talk, we will cover how Snowflake offers you a flexible development environment for developing Python data pipelines, performing transformation at scale, orchestrating and deploying your pipelines at scale. Topics we’ll cover include: – Ingest: Data source APIs, Snowflake file-to-read and ingest data of any format when files arrive, with sources outside Snowflake – Develop: Packaging (artifact repo), Python runtimes, IDE (Notebook, vscode) – Transform: Snowpark pandas, UDFs, UDAFs – Deploy: Tasks, Notebook scheduling

Connecting machines and structuring industrial data has long been one of the toughest challenges in smart manufacturing. Before unlocking the power of AI, large language models, or advanced analytics, companies must first solve the foundational task of harmonizing and organizing their data—without this, bad data only leads to bad AI.

This session covers the journey from building a Unified Namespace as the data foundation to scaling predictive use cases such as maintenance, quality optimization, and process improvements. Using customer stories from discrete and process manufacturing, we will show howDXC &Snowflake enables enterprises to connect IoT data at scale, establish a harmonized taxonomy across global operations, and drive measurable business outcomes.

By unifying diverse industrial IoT and enterprise data into a governed data layer, the Unified Namespace enables creation of an operational digital twin—a live, authoritative representation of manufacturing systems and assets that fuels scalable AI use cases like predictive maintenance, autonomous control, and AI-driven shop floor assistance. Attendees will learn howDXCs &Snowflake’s IoTbest-practicespower OT/IT convergence, continuous digital twin evolution, and AI-driven operational excellence.

Collecting and analyzing data is at the heart of every pharmaceutical R&D organization. As a result, we at Merck KGaA store large amounts of very diverse data – from assay results in early research, to operational data from clinical trials, human clinical trial data and data related to regulatory submissions. In the upcoming era of artificial intelligence (AI), making this data available to AI systems at scale is a strategic imperative. For this reason, we have formed a cross R&D workstream to modernize our compute & story ecosystem. In this presentation, we will explain the approach taken, the main challenges faced and how we are addressing them. One important component of our new ecosystem is Snowflake, where we leverage automation and blueprints to enable a consistent technical foundation across the different R&D domains.

In today's fast-paced business world, fast, reliable access to high-quality data is essential. Kuehne+Nagel addresses this by adopting Data Mesh principles, using Snowflake for managed data access. This session introduces the Kuehne+Nagel New IT Ecosystem (KNITE), a suite of platforms that replace legacy systems and implement Data Mesh principles, with Snowflake as a core component. We’ll showcase how Snowflake integrates into KNITE and highlight the features powering our Data Mesh approach.

Siemens has developed two pilots for customer-facing industrial applications on Snowflake that bring the power of OT/IT integration to life: An OEE app enabling Siemens customers to talk to their machine data and gain insights and create customised insights in a self-service manner within seconds. And a logistics insights application enabling customers to optimise the continuous reorganisation of the warehouses close to their production. Both applications use shop floor data collected through Siemens' Industrial Edge solution that can now be integrated seamlessly into the customer's Snowflake data cloud with our native connector

RSG Group – the global fitness powerhouse behind Gold’s Gym, McFIT, and JOHN REED – modernized its fragmented, manual data infrastructure into a scalable, low-maintenance analytics platform using Snowflake, Fivetran, and Coalesce. With a lean team and growing data needs across 900+ studios in 30 countries, the company replaced brittle pipelines and slow onboarding with automated ingestion, governed transformations, and self-service analytics. In this session, Head of Data & Business Intelligence Christopher Rüge will share how RSG Group reduced data integration time from 80 hours to 30 minutes, established end-to-end lineage and GDPR compliance with Coalesce, enabled data-driven decisions, and a strong foundation for AI use cases like personalization, churn prediction, and operational insights.

At this session, Sascha Urban, VP of Data at Blinkist, will reveal how his team went from data chaos to driving measurable business impact. Learn the three mindset shifts that freed up 30% of engineering time and turned a cost center into a true revenue driver.

Bayer is redefining how business questions get answered—fast, smart, and at scale. Together with ThoughtSpot, this session will share how Bayer uses ThoughtSpot on Snowflake to move beyond static dashboards and transition towards agentic analytics. With natural language querying, real-time insights, and AI-powered recommendations, Bayer enables users globally to make informed, data-driven decisions. You’ll hear how Bayer rolled out ThoughtSpot across multiple teams, trained diverse user personas, and optimized for both performance and Snowflake credit consumption.

Join us on our journey as we set out to transform a vast archive of 35,000 reports into structured, actionable data. Guided by the power of Snowflake Data Cloud and Document AI, we trained intelligent models to extract and organize critical information. Our adventure concludes with a seamless interface, where business users can easily access and leverage these insights. Discover how our team’s innovative path turned complexity into clarity, unlocking new value for the organization.

This session provides an update on the new features in the Snowflake Horizon Catalog as well as a live demo of some of its key capabilities. You will learn about the latest advancements in lineage, data quality management, and the ability to catalog third-party data sources in Snowflake.

Master Al-powered analytics in Snowflake. Learn how to leverage Snowflake's powerful Al SQL functions for advanced analytics on unstructured data. We'll also demonstrate how to use Semantic Views to bridge the gap between data and business understanding.

Evgenii, platform engineer at a global pharmaceutical company invites you to explore the journey in building a cloud-native Federated Data Platform powered by dbt Cloud, Snowflake, and Data Mesh principles. Learn how we defined foundational tools and standards, and how we enabled automation and self-service to empower teams across the organization.

Explore how Deloitte and Enercity developed their "Digital Twin Project" on Snowflake, showcasing its impact on operations and data-driven insights

As Germany's largest insurance groups embrace AI transformation, the challenge isn't just implementing large language models—it's building scalable, compliant infrastructure for enterprise-grade AI workflows. This session explores how Inverso, as a specialized Snowflake MSP, is revolutionizing insurance operations by combining Snowflake's data platform with cutting-edge AI to create production-ready solutions for automated claims processing and policy interpretation.

With Snowflake's integration service, Snowflake is providing enterprises with open, extensible and secure data integration capabilities that enable real-time, scalable and bi-directional data movement. Powered by Apache NiFi, this service offers customers the option to use a self-contained data plane in Snowpark Container Services, as well as the ability to run BYOC data planes in the customer’s cloud VPC. We will dive into the platform architecture in this technical session.

In this talk, we present our Proof of Concept (PoC) for Cortex Analyst on Snowflake, enabling interactive queries on complex geospatial data enriched with sociodemographic, market, and infrastructure information. An AI-powered text-to-SQL interface translates natural language queries into SQL in real time, with results shown in tables and visualizations. All of this leverages Snowflake’s built-in security and governance features.

Rethink how you build open, connected, and governed data lakehouses: integrate any Iceberg REST compatible catalog to Snowflake to securely read from and write to any Iceberg table with Catalog Linked Databases. Unlock insights and AI from semi-structured data with support for VARIANT data types. And enjoy enterprise-grade security with Snowflake's managed service for Apache Polaris™, Snowflake Open Catalog.