Databricks targets the data lakehouse in media and entertainment

Databricks on Thursday released a new Data Lakehouse platform optimized for the media and entertainment industry.

San Francisco-based Databricksis a pioneer in the development of the concept of data lakehouse, a technological approach that combines the capabilities of a data lake with those of a data warehouse.

During 2022, Databricks deployed a series of data lake platforms for specific industries, including healthcare and life sciencesas well as retail and consumer goods. The vendor’s goal with the industry-specific platforms is to provide services that enable a data lake for organizations in the targeted industry.

For example, in media and entertainment, the Databricks data lakehouse is now optimized to handle the large volume of unstructured video content that characterizes the industry.

Among the companies using the Databricks platform is Japanese gaming giant Sega, which operates globally.

Felix BoulangerHead of Data Services at Sega Europesaid the vendor has always siled data in different places, including apps and game development studios.

Sega uses data for sales as well as in-game activity which can be used to improve user experience. Prior to using Databricks, it was difficult for Sega’s data scientists and developers to access data, and they often had to communicate with remote company people in different locations to request access to specific data. .

“What Databricks has done is sort of democratized our Data across the world, which means anyone can now access all of this data more or less whenever they want, which has made life a whole lot easier,” Baker said.

How Sega uses the Databricks data lakehouse

One of the attractive attributes of the Databricks data lakehouse for Baker is that the platform is built on a solid foundation in Apache Spark.

Before using Databricks, pulling data from different systems for analysis was often a time-consuming batch process, Baker said. With Spark, data can be streamed from games to the Data Lakehouse and available for reporting and analysis in seconds.

“When we were just using batch processing, the data was never particularly up-to-date and it might take an hour or two before you actually saw it,” Baker said.

By making data readily available, one application the data lakehouse has enabled for Sega is improving game balance.

Game balancing is adjusting the abilities of a specific character or game resource, which can adversely affect performance in multiplayer games, unfairly disadvantage some players. Game balancing aims to calibrate the game so that it is fair for all players.

“A lot of the data stored in Databricks’ Data Lakehouse helps developers determine how people play their games, and it’s used a lot for game balancing,” Baker said. “Developers use this data to make decisions to improve the end-user experience.”

Databricks Data Lakehouse Optimizations for Media and Entertainment

The challenge for media and entertainment companies is not to amass data. Rather, it’s about being able to use all the data, according to Steve Sobel, global head of communications, media and entertainment at Databricks.

“This is where the data lakehouse comes in with the ability to take any data, prepare it for any use case, from AI to BI [business intelligence] and do it exceptionally fast,” Sobel said. “That’s where we see tremendous value for our clients in the media space who are looking to really accelerate the work they do around all things personalization. , ad and content optimization. life cycle.”

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