Databricks Democratizes Data and Reduces Infrastructure Costs for Eyeview

We are happy to announce that Eyeview has selected Databricks as their enterprise data platform — doubling the pace of innovation and development of new product features through faster data processing and simpler operations.

You can read the press release here.

Eyeview is a video advertising technology company and a leader in providing brands with higher return on investment (ROI) on their video advertising spend.  Data is an integral part of Eyeview’s platform, enabling the planning and optimization of video advertising campaigns for Eyeview’s customers. Eyeview gleans consumer knowledge and business intelligence data from first and third party sources to create thousands of ad permutations for different audiences, personalizing the ads based on factors such as location, shopping habits, and browsing history.

After evaluating multiple solutions including a Hadoop-based platform and AWS’ data warehousing offering which was already in use, Eyeview selected Databricks to meet its need for an enterprise data platform that could natively support multiple big data capabilities at scale including data warehousing, machine learning, both SQL and programmatic interfaces, and ultimately streaming analytics.

Since implementing Databricks for its data warehouse and ad hoc analytics needs, Eyeview has experienced the following improvements in performance and cost efficiency:

• 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.

Download this case study to learn more about how Eyeview is using Databricks.

To try out Databricks for yourself, sign-up for a 14-day free trial of Databricks!