I am often asked about the state of data science and where we sit now from a maturity perspective. The answer is pretty interesting, especially now that it’s been more than a year since COVID-19 rendered most data science models useless — at least for a time.
COVID forced companies to make a full model jump to match the dramatic shift in daily life. Models had to be rapidly retrained and redeployed to try to make sense of a world that changed overnight. Many organizations ran into a wall, but others were able to create new data science processes that could be put into production much faster and easier than what they had before. From this perspective, data science processes have become more flexible.