FunPlus gains new player insights to optimize gaming with Databricks

Overview

Gaming company FunPlus migrated from Snowflake to the Databricks Data + AI Platform with Delta Lake, Unity Catalog and MLflow for BI dashboards and predictive player-behavior models, cutting operational costs 40%, improving BI efficiency 20%, and increasing data engineer productivity 48%.

The challenge

FunPlus's legacy Snowflake data warehouse demanded significant manual intervention across diverse data sources (PostgreSQL, S3, MySQL, MongoDB and external APIs), requiring practitioners to create multiple access credentials, add partitions and write custom code, and making it hard to deploy ML-based player insight models effectively.

The solution

With the help of Koantek, FunPlus migrated to the Databricks Data + AI Platform, using Delta Lake to connect scattered data sources with data versioning and schema enforcement, SQL Serverless for analyst queries, Unity Catalog for metadata management and role-based access control, and MLflow for experimentation and deployment of player-behavior prediction models. FunPlus also adopted generative AI tools including AI/BI Genie and Streamlit for natural-language querying and interactive data apps.

Reported business value

Databricks improved FunPlus's data engineering productivity by 48%, made BI-related processes 20% more efficient, and cut operational costs by 40%. FunPlus also achieved an API stability of 99.9%, enabling a seamless and engaging personalized player experience.