Improving Public Health Surveillance During COVID-19 with Data Analytics and AI
For many health organizations, building this analytics muscle has been a slow burn. The good news: powerful cloud-based software solutions, like Databricks Unified Data Analytics Platform, are accelerating this transformation with the tooling and scale needed to analyze large volumes of health data in minutes. With these fundamental data problems solved, health organizations can refocus their efforts on building analytics and ML products instead of wrangling their data. One example is the COVID-19 surveillance solution developed on top of Databricks, which is being deployed in a number of state and local government health departments, as well as by a number of hospitals and care facilities across the U.S. This is a brief demo of our public health surveillance solution. In the demo, we show how to take a data-driven approach to adaptive response, or in other words, apply predictive analytics to COVID-19 datasets to help drive more effective shelter-in-place policies. With this solution on Databricks we’re able to yield important insights in a short amount of time and, as a cloud native offering, it can be deployed quickly and cost effectively at scale. We recently launched this program in one of the largest state government health departments in the country, and we had it running and delivering insights in less than two hours."""
Session ID: Presentation Type: On-Demand Session (Recorded)
Date / Time: [Content On-Demand] @ On Demand ET (US)
Presented by:Databricks is the data and AI company. Thousands of organizations worldwide rely on Databricks’ open and unified platform for data engineering, machine learning and analytics. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to solve the world’s toughest problems. Click for more details and additional sessions and content.
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