Analytics for Games
Analytics for games has changed dramatically over the past 15 years. The advent of mobile gaming platforms has produced a flood of new data points and the need to update, personalize, and upsell the gaming experience in order to retain and grow market share. In response to online gaming, most traditional console platforms have also moved to a hybrid in-console/online experience. The transactional data volumes in modern games - - many of which involve complex. evolving, online multi-player environments -- means that release-and-forget design is a thing of the past.
Gaming and Big Data
Big Data for gaming is, at its simplest, the raw material that provided insight into gaming consumer behavior. It combines demographic and social media data with in-game behavior data to provide a look into how customers interact with games, who they play with, and where and when they play, and who they play with.
By mining this data with gaming analytics, gaming companies can improve the playing experience with targeted personalization, ongoing stimulation and motivation, and multi-device access.
Analytics for Games and Snowflake
Snowflake's high elasticity platform can handle disparate data sources (structured and semi-structured data such as JSON), high concurrency, and high data volumes. With Snowflake, gaming analysts can access constant insights to improve game play, deliver personalized game experiences, and drive revenue.
With Snowflake, you can combine multiple platforms for players, transactions and events into a single location and scale compute up, down, out and automatically on the fly -- all with zero management and full security.