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Big Data Analytics Lifecycle

Big Data Analytics Lifecycle
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Author(s): Smrity Prasad (Christ University, India)and Kashvi Prawal (Penn State University, USA)
Copyright: 2024
Pages: 19
Source title: Big Data Analytics Techniques for Market Intelligence
Source Author(s)/Editor(s): Dina Darwish (Ahram Canadian University, Egypt)
DOI: 10.4018/979-8-3693-0413-6.ch003

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Abstract

Big data analysis is the process of looking through and gleaning important insights from enormous, intricate datasets that are too diverse and massive to be processed via conventional data processing techniques. To find patterns, trends, correlations, and other important information entails gathering, storing, managing, and analyzing massive amounts of data. Datasets that exhibit the three Vs—volume, velocity, and variety—are referred to as “big data.” The vast amount of data produced from numerous sources, including social media, sensors, devices, transactions, and more, is referred to as volume. The rate at which data is generated and must be processed in real-time or very close to real-time is referred to as velocity. Data that is different in its sorts and formats, such as structured, semi-structured, and unstructured data, is referred to as being varied.

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