Introduction
This is Johann from the Global Engineering Department of the GLB Division. I wrote an article summarizing the content of the session based on reports from Mr. Kanemaru participating in Data + AI SUMMIT2023 (DAIS).
A presentation titled "How Rec Room Processes Billions of Events Per Day with Databricks and RudderStack" was held, introducing how Rec Room utilizes Rudder Stack and Databricks to process 10 billion events per day and improve user gaming experiences. The speakers were Albert, a Senior AI Engineer at Rec Room, and Lewis Mbae, the leader of the Customer Engineering Team at Rudder Stack. The theme and purpose of this presentation are to introduce how Rec Room uses Rudder Stack and Databricks to process 10 billion events per day and improve user gaming experiences for those interested in data processing, game development, and data analysis. This blog is structured in one part, and this is the first part.
Rec Room's Data Team Processing 10 Billion Events per Day
Rec Room's data team works to process various in-game events in real-time to improve user gaming experiences. To do this, they focus on the following fundamentals of data processing:
Data collection
Data transformation
Data science
To efficiently perform these data processing tasks, RecRoom utilizes two technologies: RouterStack and Databricks.
Data Processing with Rudder Stack and Databricks
Rudder Stack is an open-source data infrastructure that can collect data and send it to multiple data storage and analysis tools. In Rec Room, Rudder Stack is used to collect in-game event data and send it to Databricks. Databricks is an integrated analytics platform for efficiently processing big data and machine learning. Rec Room's data team uses Databricks to process event data in real-time and provide feedback to improve user gaming experiences. Specifically, the following processes are performed:
Send event data collected by Rudder Stack to Databricks
Transform and format data in Databricks for analysis
Extract insights using data science to improve user gaming experiences
Optimize in-game features and content based on insights
Incorporating the Latest Concepts, Features, and Services
Rec Room's data team is further improving data processing efficiency by incorporating the latest concepts, features, and services. For example, they are using the latest machine learning technologies to predict user behavior in the game and personalize gaming experiences. Additionally, the data team is focusing on data visualization and dashboard creation, making it easier for game developers and marketing professionals to utilize data. Rec Room's data processing efforts serve as a reference case not only for the gaming industry but also for businesses looking to grow by leveraging data. The efficiency of data processing using Rudder Stack and Databricks will continue to be an important theme for many companies in the future.
Summary
We introduced how Rec Room utilizes Rudder Stack and Databricks to process 10 billion events per day and improve user gaming experiences. By mastering the basics of data processing and leveraging the latest concepts and features, it is possible to provide the best gaming experience for users. RecRoom's data processing efforts will continue to be a reference case for businesses looking to grow by leveraging data.
Conclusion
This content based on reports from members on site participating in DAIS sessions. During the DAIS period, articles related to the sessions will be posted on the special site below, so please take a look.
Translated by Johann
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