ZeniMax Wins the Big Data Game with a Pentaho-Based Single Version of the Truth

ZeniMax won the 2017 Pentaho Excellence Award in Big Data, a category that recognizes organizations for leveraging Big Data technologies like Hadoop, NoSQL or Spark to overcome their data challenges and create business value.

Big Demands on Big Data in Highly Competitive Gaming Industry

ZeniMax Media publishes original interactive entertainment content for gaming consoles, computers and handheld/wireless devices. The company operates some of the world’s most acclaimed development studios and creates award-winning video games, including The Elder Scrolls, Fallout, Dishonored, DOOM, QUAKE, Wolfenstein, Prey, The Evil Within and RAGE.

ZeniMax wanted to harness the power of its massive data volumes to gain insights about its customers and improve its operations. But it lacked a single view of its data environment to understand user behavior across games.

Massive Data Volumes Scattered Across a Complex Data Environment

Huge quantities of data—roughly 30 to 40 GB of new data generated every 5 minutes, plus 5 years of legacy data—were managed in various silos, including two e-commerce platforms and multiple data repositories across its game studios. The company uses Redshift for data warehousing and a combination of Cloudera in its data centers and Databricks in AWS.

Data from these disparate and fragmented sources had to be manually stitched together to generate a single view needed for data-driven decision making. This cumbersome process consumed too many resources and resulted in fragmented metrics and KPIs.

Single View of Data Used to Mine Insights into Player Behaviors, Preferences

In 2014, ZeniMax embarked on a mission to create a single view of their data. The company needed a data integration solution that provided flexibility in a complex data environment.

They found that solution in Pentaho Data Integration. The Data Engineering team first created a single view of their data warehouse by populating it with key game and business-focused metrics. The team then established KPIs and created common definitions across all games. Automating SQL workloads freed up data scientists’ time considerably.

ZeniMax now has a better understanding of player behavior and preferences, such why a player stops playing a certain game, which features they prefer, and when and why a player spends money. Ultimately, the company plans to leverage this data to segment players and incentivize them with custom promotional offers which will drive user engagement, improve revenue and greater participation.

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Jonathan Shafer

Senior Product Customer Marketing Manager