![]() The on-the-ground issues Odisha was facing were critical. The problem was that Odisha didn't have the data or the tools that were needed to do the job. Finally, it wanted risk assessment tools. It also wanted analytics that could help it assess what the patient loads would be on healthcare facilities like hospitals and clinics, and how it could best manage quarantines and other measures needed to combat the advance of COVID. Odisha wanted tools to measure the aggressiveness of the pandemic and determine how the pandemic was spreading. The east Indian state of Odisha found itself in this situation. In some instances, new types of analytics data and applications had to rapidly be created to deal with the COVID crisis. "What they found with the pandemic was that these models had to be retrained and additional data sources added before the models could start accurately predicting the new normal traffic pattern that resulted from COVID." "in one case, airports had been using predictive modeling to understand and improve aircraft traffic flow," Tareen said. In other cases, companies lacked data and applications altogether to deal with the COVID crisis, and they had to find ways to obtain the data they needed and develop new analytics models quickly. In some cases, existing data models that had been so reliable suddenly began to underperform to the point that they needed tweaking. ![]()
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