Snowflake’s Data Cloud offers a powerful, scalable platform that enables organisations to efficiently manage and utilise their data across various cloud environments.
We caught up with the Snowflake team to learn more about their innovative initiatives and excitement of working with ThinkSport.
Can you share any recent advancements or projects that Snowflake is particularly proud of?
At Snowflake Summit in June 2024 we introduced Cortex AI, a fully managed service to enable enterprise AI with no-code development, serverless fine-tuning, and managed services for building AI applications with chat-with-data interfaces. Key features include Cortex Analyst – through which business users can interact with structured data using natural language, and the AI & ML Studio – which facilitates no-code AI development opportunities for users of all technical levels. Cortex AI was designed to drive business impact in the following ways: 1) Increased Accessibility – makes AI tools accessible to all users, regardless of technical expertise, 2) Enhanced Productivity – accelerates AI development and deployment, reducing time and co3sts, 3) Improved Security and Compliance – provides robust data security and governance, ensuring compliance with sport and other industry standards, and 4) Scalability and Efficiency – optimizes AI models for specific tasks, further reducing latency and costs.
How does Snowflake collaborate with other organisations and stakeholders to drive innovation?
Cortex AI was developed to enable Snowflake customers and partners to maximize AI/ML-based innovation opportunities. Within sports, we’ve started to see this innovation unfold across multiple areas. For example, we’ve started to see clubs leverage Cortex AI to build, train, and deploy models to help inform recruiting, player health and safety, and on the pitch strategies. We’ve also seen clubs leverage Cortex AI to inform ticketing, sponsorship, and concession revenue driving strategies. We’ve seen sportsbooks use Cortex AI to enable predictive analytics modelling for the purpose of detecting fraudulent or problem gambling behavior. Snowflake’s Data Clean Rooms feature has also enabled sports leagues, media, and marketers to optimise sponsorship campaign targeting and messaging strategies for the purpose of better serving the fan as well as brand goals. We’ve seen all of these entities as well as ticketing and merchandise providers leverage the Snowflake AI Sports Data Cloud to build a 360-degree of fans that factors fan engagement across owned and operated as well as partner channels. This is an important step because a complete view of each fan is required for enabling successful personalisation outcomes across any activation.
Can you identify the most influential idea currently under development or exploration that, in your opinion, has the potential to redefine the future of sport?
Snowflake is looking into numerous new opportunities for driving more value for sports customers on a regular basis. One area of focus currently is how we can better serve sports customers’ data needs in relation to video. Video is an important asset for multiple sports use cases – from driving fan engagement, to establishing player training regimens, to enabling meaningful advertising integrations. Snowflake currently helps customers leverage their video assets by enabling more efficient media supply chain workflows. We are also looking into ways that we can further support video tagging, cataloguing, search, and AI/ML-driven curation opportunities.