Databricks Inc. is continuing its recent campaign to court customers in vertical industries with today’s announcement of an analytics platform targeted at the media and entertainment industry.

The company, which sells an analytics platform based on the Apache Spark framework, said the Lakehouse for Media & Entertainment addresses a set of common industry use cases such as recommendation engines, customer lifetime value, churn metrics, quality of experience and advertising optimization.

“Lakehouse” is a Databricks-coined term for a data repository that combines elements of both a structured data warehouse and an unstructured data lake. With support for real-time processing, business intelligence and machine learning, the platform will allow media organizations to incorporate a variety of unstructured data types – including images and video — to understand better how their products are used.

A pre-built recommendation engine lets media firms create more personalized experiences using content recommendations enabled by machine learning. A customer lifetime value calculator can be used to identify the most valuable customers by analyzing spending patterns and retention. A pre-built streaming quality-of-service toolset analyzes both streaming and batch data sets to help optimize viewer experiences and toxicity detection for gaming leverages natural language processing for the real-time detection of offensive language in user comments and chats during gaming sessions.

The platform is launching with third-party analytics services from Amazon Web Services Inc., video quality control software from Cognizant Technology Solutions Corp., data services from Lovelytics and Fivetran Inc. and a training platform from Labelbox Inc.

Databricks said early customers for the lakehouse include Acxiom Corp., Sega Sammy Holdings Inc.,  Discovery Inc. and Condé Nast International Inc.

This is Databricks’ fourth industry-specific lakehouse. Earlier this year it announced versions for retail, financial services and healthcare.

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