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Event processing is a method of tracking and analyzing (processing) streams of information (data) about things that happen (events), [1] and deriving a conclusion from them. Complex event processing ( CEP ) consists of a set of concepts and techniques developed in the early 1990s for processing real-time events and extracting information from ...
A data processing system is a combination of machines, people, and processes that for a set of inputs produces a defined set of outputs. The inputs and outputs are interpreted as data , facts , information etc. depending on the interpreter's relation to the system.
Artificial intelligence (AI), in its broadest sense, is intelligence exhibited by machines, particularly computer systems.It is a field of research in computer science that develops and studies methods and software that enable machines to perceive their environment and use learning and intelligence to take actions that maximize their chances of achieving defined goals. [1]
Also simply application or app. Computer software designed to perform a group of coordinated functions, tasks, or activities for the benefit of the user. Common examples of applications include word processors, spreadsheets, accounting applications, web browsers, media players, aeronautical flight simulators, console games, and photo editors. This contrasts with system software, which is ...
Supervised learning algorithms build a mathematical model of a set of data that contains both the inputs and the desired outputs. [48] The data, known as training data, consists of a set of training examples. Each training example has one or more inputs and the desired output, also known as a supervisory signal.
Analytics is the systematic computational analysis of data or statistics. [1] It is used for the discovery, interpretation, and communication of meaningful patterns in data, which also falls under and directly relates to the umbrella term, data science. [2] Analytics also entails applying data patterns toward effective decision-making.
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This data is being used to increment internal companies' data to improve business processes and decision making, for AI training and for supplementing organization’s services or products. [10] Wherein, external DaaS uses data licensed from a vendor, which is supplied to a customer on demand.