Data scientists are spending a significant portion of their work time on tasks that could be streamlined with better tools. A recent market research post highlights that many data scientists feel they are using systems designed for an earlier era of the web, which are not optimized for modern data science needs. This inefficiency leads to a considerable time sink, with some estimating that up to 80% of their work time is spent on tasks that could be automated or improved. The post seeks to identify the most time-consuming problems in data science work, aiming to develop side projects that address these inefficiencies.
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