McGraw-Hill Optimizes Analytics Workloads with Databricks

Опубликовано 30 мая 2018, 17:48

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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