Managing 200TB of player data required heavy manual oversight. Now, serverless pipelines let scientists deploy models themselves.
A sports analytics startup processes up to 200 terabytes of football data per season from 14 different sources, including high-frequency sensor tracking, scouting reports, and contract financials.
The emergence of high-frequency player tracking data overwhelmed their fragmented infrastructure, which relied on a patchwork of custom orchestration...
“Visibility was limited. We only surfaced issues after they had already impacted downstream users.”
SumerSports is a sports analytics company that provides a data-driven platform to help professional and collegiate sports teams make informed roster decisions within salary cap constraints.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
SūmerSports's Sports analytics is part of this use case:
Related implementations across industries and use cases
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Coaches had 30 seconds between points, but insights took hours. Now, AI analyzes live telemetry to answer tactical questions courtside.
A one-second delay was too slow for live sports. Cloud inference now delivers stats 10x faster, powering 60+ AI initiatives.
A one-second delay was too slow for live sports. Cloud inference now delivers stats 10x faster, powering 60+ AI initiatives.
Telemetry from 6M machines was trapped in internal silos. Unifying it into a shared platform lets customers deploy predictive AI.
Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Managing 200TB of player data required heavy manual oversight. Now, serverless pipelines let scientists deploy models themselves.
A sports analytics startup processes up to 200 terabytes of football data per season from 14 different sources, including high-frequency sensor tracking, scouting reports, and contract financials.
The emergence of high-frequency player tracking data overwhelmed their fragmented infrastructure, which relied on a patchwork of custom orchestration...
“Visibility was limited. We only surfaced issues after they had already impacted downstream users.”
SumerSports is a sports analytics company that provides a data-driven platform to help professional and collegiate sports teams make informed roster decisions within salary cap constraints.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
SūmerSports's Sports analytics is part of this use case:
Related implementations across industries and use cases
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Coaches had 30 seconds between points, but insights took hours. Now, AI analyzes live telemetry to answer tactical questions courtside.
A one-second delay was too slow for live sports. Cloud inference now delivers stats 10x faster, powering 60+ AI initiatives.
A one-second delay was too slow for live sports. Cloud inference now delivers stats 10x faster, powering 60+ AI initiatives.
Telemetry from 6M machines was trapped in internal silos. Unifying it into a shared platform lets customers deploy predictive AI.
Protecting users from harmful on-device AI required internet. A powerful safety AI now runs directly on the PC, guarding users even when offline.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.