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McGraw-Hill Optimizes Analytics Workloads with Databricks

Performing data science workloads on data from disparate sources – data lake, data warehouse, streaming, and more – creates challenges for organizations needing to use their data to drive operational and product improvements. Textbook publisher McGraw-Hill needed to remove such data silos so it could transform its business model to accommodate a growing focus on digital learning. Specifically, the company wanted the ability to quickly perform complex analytics operations and enable collaboration between business analysts, data engineers, and data scientists.

McGraw-Hill deployed Databricks, a unified analytics platform that allows it to work efficiently with streaming data as well as historical data stored in data lakes on Amazon S3 and in multiple data warehouses. In this webinar, you’ll learn how Databricks, developed by the original creators of Apache Spark™, allows McGraw-Hill to analyze streaming and historical data at a scale and speed their previous solution simply couldn’t provide. Data science workloads that used to take weeks, now take hours.

Using Databricks, McGraw-Hill securely transformed itself from a collection of data silos with limited access to data and minimal collaboration to an organization with democratized access to data and machine learning. This ultimately enables its data teams to rapidly identify usage patterns predicting student performance, so they can make timely enhancements to the software that proactively guide at-risk students through the course material.

Join our webinar to learn:
  • How a cloud-based unified analytics platform can help your company perform analytics faster, at lower cost.
  • How to mitigate challenges presented by data silos so data science teams can collaborate effectively.
  • How to implement data analytics infrastructure to put models into production quickly
When: Available On Demand (please register to view)

Who Should Attend:
Attendance is encouraged for Data Scientists, Data Engineers, heads of data warehousing, heads of BI, heads of analytics, data architects, enterprise architects, cloud architects, data integration experts, and BI experts.

AWS Speaker: Pratap Ramamurthy, Partner Solutions Architect
Databricks Speaker: Brian Dirking, Sr Director of Partner Marketing
Customer Speaker: Matthew Ashbourne, Lead Software Engineer, McGraw-Hill Education