Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
