Data analytics is related to extracting information from observations, measurements, or experiments about a phenomenon or subject of interest for different purposes, such as interpretation of the data, decision making, diagnosis, and prediction [1]. A classification of the entire field of big data analytics is difficult to make and can be based on a variety of criteria. One classification related to the depth of the analysis is presented by Blackett [2], identifying three levels: descriptive, predictive, and prescriptive analytics. Descriptive analytics uses past data to analyze what has occurred, while predictive analytics focuses on forecasting future trends and determining probabilities of occurrence mainly through the application of different statistical techniques or data mining algorithms for pattern extraction. Prescriptive analytics facilitates decision making and optimization of complex systems.

• Todor Cooklev
• Vladimir Poulkov
• Daniel Bennett
• Krasimir Tonchev

IEEE Aerospace and Electronic Systems Magazine, vol. 33, no. 5-6, pp. 44-55, 2018, DOI: 10.1109/MAES.2018.170108.

https://ieeexplore.ieee.org/document/8361207