June 26-29, 2023 | USA
How you approach data will define what’s possible for your organization. Data engineers, data scientists, application developers, and a host of other data professionals who depend on the Snowflake Data Cloud continue to thrive thanks to a decade of technology breakthroughs. But that journey is only the beginning.
Attend Snowflake Summit 2023 to learn how to access, build, and monetize data, tools, models, and applications in ways that were previously unimaginable. Enable seamless alignment and collaboration across these crucial functions in the Data Cloud to transform nearly every aspect of your organization.
At Summit, you’ll hear all about the latest innovations coming to the Data Cloud, and learn from hundreds of technical, data, and business experts about what’s possible for you and your organization in a world of data collaboration.
October 3-5, 2023 | USA
Learn how leading innovators are harnessing the power of data to accelerate business outcomes.
DataDriven23 is a modern data management conference where the world's leading data innovators come together -- where experts, thought leaders, and peers connect and gain the expertise to unlock the value of data, stay ahead of the curve, and maximize impact on their businesses every day. Reltio, together with leading partners and experts, brings this inspiring event to data innovators.
November 16, 2023 | USA
Architecture is the foundation of every organization's data strategy - it must align with the short and long term goals of the organization whilst creating an environment that supports data collection, processing, analytical & ML workloads.
DataNext Architecture will deep dive into how organizations are using their architecture to create the foundation to become truly data driven. Showcasing how architecture underpins the value that an organization derives from its data initiatives.
July 26-28, 2023 | Singapore
The avalanche of data generated by companies and their customers should be a competitive advantage, but most companies are struggling to manage it all. Data accessibility, quality, governance and security are all critical for operationalizing machine learning applications, so the stakes are high. Emerging frameworks are helping us come to grips with these issues but the answers go beyond just technology.