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Ready to use data science clusters

Media companies today are looking for ways to control access to data and machine learning (ML). Ready-to-use data science clusters help to unlock the potential of shared, consumable data while accelerating time to value and lowering total cost of ownership.

Databricks

Unified Data Analytics Platform

Databricks Unified Data Analytics Platform is a cloud-based service for running your analytics in one place, from data pipelines to ML. It provides data science and engineering teams out-of-the-box clusters with optimized Apache Spark and various ML frameworks. These clusters are coupled with collaboration capabilities to improve productivity across the ML lifecycle. Databricks also incorporates Delta Lake, which makes data lakes running on Amazon S3 instantly analytics ready.

Databricks provides flexible and agile ways to analyze data in real time, enabling the ability to draw insights that increase audience engagement. Provide content recommendations that drive personalized experiences by analyzing viewer, purchase, and behavioral data. Optimize scheduling of media streams and identify factors, such as stream quality and content preference that influence viewer loyalty. This leads to increased customer satisfaction and reduced churn. Realize the strengths of Databricks Unified Data Analytics Platform through the following product features:

  • Collaborative notebooks
  • Access to preconfigured ML environments with frameworks such as TensorFlow, Keras, and Horovod
  • Complete ML lifecycle and optimized environments
  • Reliable data lakes
  • Highly efficient and fast data pipelines
    • Learn more about Databricks Unified Data Analytics Platform

    How it works

    Additional resources from Databricks

    McGraw-Hill Education

    McGraw-Hill Education is a 129-year-old educational company that faced several innovation challenges, specifically data access, processing, and scale. By adopting Databricks, the company was able to reduce its infrastructure complexity, improve cluster management, and build out automated workflows. As a result, McGraw-Hill reduced its total cost of ownership by 30%. They also accelerated their time to value through rapid delivery of innovative solutions to over 5.5 million students.

    Having an agile innovation workflow is critical for McGraw-Hill Education. Databricks Unified Analytics Platform is at the center of our ecosystem and underpins our innovation pipeline and workflows.

    Alfred Essa, VP of Research and Data Science, McGraw-Hill Education