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Digital transformation is a period of many changes for industries with the rise of many innovative technologies that gained application within the plants. However, it was due to several technologies arising from a knowledge area called Big Data that the technological revolution began to gain new proportions.
Within an industrial operation, there are many variables that need to be monitored and that can be better managed through data control.
Efficient processing of large amounts of data and extracting knowledge from them are the main goals achieved using Big Data methods. In an industrial installation, the amounts of structured and unstructured data that must be extracted and processed are immense.
Big Data becomes primarily responsible for extracting useful knowledge from structured and unstructured data. And by extracting and processing this information, industries are able to better understand their present and prepare for the future.
It is very common for Big Data technology to be used in industrial plants with the aid of Machine Learning algorithms. The combination of techniques and methods from these two areas (Big Data and Machine Learning) allows the extracted data to be processed and interpreted, generating useful information for obtaining insights, which could not be achieved without automating the process of obtaining information. high-level knowledge from raw data and information.
Pattern recognition and prediction calculation performed by machine learning algorithms can be applied in the most different disciplines within an operation or process. The use of these algorithms allows companies to have the necessary tools to understand their market and segmentation, have data help for decision making, recognition of recurring patterns from past data and predictions of possible future scenarios.
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