Eyeview, a video advertising technology company, struggled to scale with business growth because its legacy systems could not cope with surging data volumes upwards to 1.5TB/day. A single query across all of the user segments often required several hours, which was not acceptable to its business needs. Additionally, Eyeview lacked a platform with native machine learning support, preventing its team from fully leveraging advanced analytics.
With Databricks, Eyeview can explore and visualize data rapidly, enabling its team to build more accurate machine learning models in shorter development cycles. Databricks also reduced Eyeview’s DevOps costs by simplifying the provisioning of Apache® Spark™ clusters on-demand and lowered AWS infrastructure costs with native support for spot instances.
- Reduced query times on large data sets by a factor of 10, allowing data analysts to regain 20 percent of their workday from waiting for results.
- Sped up data processing by fourfold without incurring additional operational costs.
- Doubled the pace of product feature development, from prototyping to deployment, by increasing the productivity of the engineering team with faster and easier management of Spark clusters.