Data exploration is the step where data analysts use visual exploration to understand what is in a dataset and the characteristics of the data. It is intended to extract knowledge from large amounts of data, by automatic or semi-automatic methods. It proposes to use a set of algorithms derived from various scientific disciplines such as statistics, artificial intelligence, and computer science to build models from the data and to find interesting structures or reasons according to previously established criteria, while extracting as many insights as possible. Industrial or operational use of this knowledge in the professional world can solve a wide range of problems, such as customer relationship management, fraud detection, and website optimization.
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