A strong Enterprise Data Foundation (EDF) is the backbone of scaling innovation and delivering measurable business impact. Establishing such a foundation requires more than technology investment; it demands strategic intent, dedicated resources, and often a distinct data function that bridges IT with business teams to enable real outcomes. Companies that progress along the data maturity curve consistently outpace their peers in growth, efficiency and innovation. Unified, high-quality data reduces the time spent searching for answers and increases the time available for acting on insights. As AI and automation become mainstream, only organisations with robust data foundations will truly thrive.
This session will explore what EDF means for businesses today, share cross-industry maturity insights, highlight success stories and outline the strategic considerations leaders must adopt to build resilient data foundations and unlock enterprise-wide impact.

Organizations transitioning from QlikSense to Power BI often face a critical gap: while Power BI excels in visualization and analytics, it lacks native ETL capabilities. Many enterprises have legacy Qlik ETL scripts (QVS files) that power their existing dashboards, and migrating these to a modern, scalable data transformation layer is essential for continuity and performance.

This session presents an AI-driven approach using Large Language Models (LLMs) to automate the migration of Qlik ETL logic into Snowflake-based SQL transformations. Snowflake serves as the data transformation engine, enabling native pass-through query execution for improved performance and reduced operational costs. The architecture supports seamless integration with Power BI, ensuring that transformed data is readily available for reporting and analytics.

We will explore the technical design, the role of LLMs in parsing and translating Qlik scripts, and the challenges encountered—such as handling complex expressions, maintaining semantic fidelity, and optimizing for Snowflake execution. Real-world outcomes will be shared, including accelerated migration timelines, reduced manual effort, and enhanced data pipeline reliability.

Attendees will gain practical insights into how AI-powered automation can bridge the ETL gap in Power BI migrations.

Learn how ServiceNow is leveraging cortex capabilities to get just-in-time insights. Join this session to discover how AI is not only simplifying data access but driving innovation and creating new possibilities for the decision-making with the integration of snowflake cortex with ServiceNow.

In this session you will hear about
1. The state of our data estate before and after onboarding Snowflake, illustrating how a robust data strategy is crucial for an effective AI strategy.
2. A use case demonstrating the utilisation of Cortex Analyst for developing Conversational AI .
3. Deep Dive into implementation of semantic model , streamlit app and Live demo of app we have built.
4.Our plans for leveraging new features of the Snowflake Data Cloud through use cases within FIL.

Learn how to bring all your data together with Snowflake Openflow to build with limitless interoperability and deployment flexibility, no matter if it’s structured, unstructured, batch or streaming data. Make your integration pipelines ready for AI and the future.

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.

Learn about the latest and greatest cost management capabilities in Snowflake to optimize your spend and get the most bang for your buck. This talk will walk through capabilities and best practices that you can use today.

Building and managing data transformation pipelines can be complex and costly. In this session, learn how to use Snowflake’s automation and managed services to streamline development, reduce infrastructure overhead, and improve debugging with built-in telemetry. Discover best practices for creating scalable, cost-efficient pipelines–and let your team can focus on insights, not maintenance.

Discover how to build and deploy a no-code, agentic AI platform with Snowflake Intelligence. See how organizations are bringing together structured and unstructured data to make insights accessible across their entire enterprise via an AI-driven agentic interface, all within Snowflake. Join us for a product overview, best practices discussion and live demo.

Snowflake recently launched new capabilities to help organizations build data agents connected to enterprise data environment. This session explores why Snowflake makes it easy to iterate, monitor and observe agentic AI systems. Learn associated best practices related to RBAC integration in agentic workflows and applications. The session will also focus on change control and environment management and the software development lifecycle within the AI agents development lifecycle.

Learn how to streamline governance and security for data and AI with Snowflake’s latest updates to Horizon Catalog. Join us for new product overviews and live demos covering interoperability, Trust Center, MFA updates, Copilot for Horizon Catalog, sensitive data, data quality, lineage, and more.

Snowflake ML enables efficient development and deployment of advanced models without any data movement. With multi-GPU support, MLOps integration and Git-based workflows, Container Runtime provides a scalable environment for training, and Snowflake ML’s products such as Model Registry and Model Serving make it easy to deploy these models in production. This session explores best practices for scalable ML workflows and the creation of production-ready ML pipelines in Snowflake.

Discover how Snowflake can help you transform your business processes into interactive, monetizable agentic applications,.In today’s rapidly evolving digital landscape, businesses are constantly seeking innovative ways to leverage their data and extract maximum value. Snowflake offers a powerful platform that enables organizations transforming their existing business processes into dynamic, interactive, and monetizable agentic applications. This paradigm shift not only extends the lifecycle and utility of your meticulously crafted data products but also unlocks new revenue streams and enhances operational efficiency.

A practical Product-oriented guide to leveraging Snowflake’s privacy-preserving Collaboration tools, including data protection policies, data clean rooms, synthetic data and more to unlock business value from sensitive data. Modern organizations are looking for ways to collaborate internally and externally on sensitive data of all kinds, while still respecting the sensitivity. Hear how Snowflake Data Collaboration capabilities enable leading organizations to obtain the best of both worlds.

Learn how to build and deploy accurate conversational apps and bring AI-powered data agents into production with ease and trust across your enterprise. Join us for new product insights, feature overviews, best practices and live demos.

Learn how to drive collaboration across your business ecosystem with the latest from Snowflake Horizon Catalog, including External Data Discovery, to effortlessly find data both within Snowflake and from external systems. See demos of the latest Internal Marketplace updates, including Organization Profiles and Request for Access, to streamline and accelerate the sharing of data, apps, and AI. Finally, learn how Iceberg Data Sharing and the Egress Cost Optimizer can increase interoperability and data availability while keeping your data sharing costs down.