by Justin Monaldo, Kacey Hertan and Yvan Aquino
A utility company deploys drones to inspect hundreds of miles of power lines. A police department pulls hours of traffic camera footage to investigate a hit-and-run accident. An urban planning team leverages camera footage to analyze pedestrian and traffic flow.
Terabytes of video data are generated every single day that can provide valuable insights into everything from operational efficiency to public safety. But almost none of it gets analyzed in any meaningful way. That’s because combing through this unstructured video data is massively time-consuming and expensive.
Imagine being able to simply apply natural language queries to video content at scale to not just find specific content—but analyze, assess, and learn from it.
Databricks can support exactly that. The approach? Treat video as a data engineering problem.
