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Big data ethics – Ethics of mass data analytics; Big data maturity model – Aspect of computer science; Big memory – A large amount of random-access memory; Data curation – Organization of collected data; Data defined storage – Marketing term for managing data by combining application, information and storage tiers
Data science process flowchart from Doing Data Science, by Schutt & O'Neil (2013) Analysis refers to dividing a whole into its separate components for individual examination. [10] Data analysis is a process for obtaining raw data, and subsequently converting it into information useful for decision-making by users. [1]
However, data has staged a comeback with the popularisation of the term big data, which refers to the collection and analyses of massive sets of data. While big data is a recent phenomenon, the requirement for data to aid decision-making traces back to the early 1970s with the emergence of decision support systems (DSS).
Analytics may apply to a variety of fields such as marketing, management, finance, online systems, information security, and software services. Since analytics can require extensive computation (see big data), the algorithms and software used for analytics harness the most current methods in computer science, statistics, and mathematics. [4]
Data-intensive computing is intended to address this need. Parallel processing approaches can be generally classified as either compute-intensive, or data-intensive. [6] [7] [8] Compute-intensive is used to describe application programs that are compute-bound. Such applications devote most of their execution time to computational requirements ...
Amir Hussain [1] [2] is a cognitive scientist, the director of Cognitive Big Data and Cybersecurity [3] (CogBID) Research Lab at Edinburgh Napier University [4] He is a professor of computing science. [4] He is founding Editor-in-Chief of Springer Nature's internationally leading Cognitive Computation journal [5] and the new Big Data Analytics ...
Learning Engineering can also assist students by providing automatic and individualized feedback. Carnegie Learning’s tool LiveLab, for instance, employs big data to create a learning experience for each student user by, in part, identifying the causes of student mistakes. Research insights gleaned from LiveLab analyses allow teachers to see ...
Open University Learning Analytics Dataset Information about students and their interactions with a virtual learning environment. None. ~ 30,000 Text Classification, clustering, regression 2015 [490] [491] J. Kuzilek et al. Mobile phone records Telecommunications activity and interactions Aggregation per geographical grid cells and every 15 ...