In a world where not only data volumes, but also the speed of data creation keep growing, data experts spend more than 80% of their time treating and preparing data. As a result, according to the “80-20 data science dilemma”, only 20% of a data scientist’s time goes into the actual modeling of data. What does this mean for your data-related projects, and how can organizations optimize their data preparation processes?
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