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Abstrakt
| This article aims to describe the KDD process, or Knowledge discovery in data, and to present some of the available software tools for this process in connection with Industry 4.0. Methods used to interpret the results in this article include research of professional sources, analysis and synthesis of acquired knowledge, and inductive and deductive approaches. In various branches of the economy, whether it is business economics or macroeconomics, we encounter an ever-increasing amount of generated data. This data can be very useful, as information can be drawn from it, which can then be used to optimize processes that lead to strengthening competitiveness in today’s very turbulent market. The more data is created, the more it can cause complications in their identification. Errors also often occur during data generation, due to which the data is not uniform. The results of this work will include a description of the eight important steps of the KDD process.. |
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