70% of all power outages are caused by weather. As you may have read in our recent blog post, due to the danger and expense associated with these outages, many Utility companies rely on weather insights to predict where outages will occur and determine the proactive positioning of rapid response and repair crews.
Today, we’d like to share an insightful article from one of our customers, Jim Foerster of DTN, on their process for helping their utility clients respond to storms more efficiently. Jim writes, the right, high-quality data is needed to train the machine-learning models that do the predictions” and we couldn’t agree more.
