Abstract
In a world where data is gathered in ever‐increasing quantities, summing more of what persons and organizations perform, and catching smallest detail of their comportment. There are three fashions to distinguish data occasionally reported as volume, variety, and velocity—the meaning of Big Data. This review aims to focus on defining Big Data and describing some of its myths and realities. The significance of big data does not focus on how much data is possessed, but what things may be performed with it. Data may be extracted from any origin and examined to detect replies that let 1) cost decreases, 2) time decreases, 3) fresh product expansion and studied offerings, and 4) smart decision making. As a magic, charming, and mysterious noun, Big Data remains an attractive novel field in both science and technology. Despite of the developed technology and open knowledge, Big Data still needs more familiarization and demystification. More developed computer skills will be needed to understand and touch its practical extent.
Highlights
The lightning blooming of the Internet and World Wide Web has conducted to huge quantities of data obtainable online [1]
Big Data may be described as bulks of data obtainable in changing levels of intricacy, produced at various rates and changing levels of confusion, that cannot be treated employing conventional engineering, treating techniques, algorithms, or any commercial off-the-shelf solutions [7, 8]
This review describes the characteristics, challenges, and solutions offered by Big Data computing
Summary
The lightning blooming of the Internet and World Wide Web has conducted to huge quantities of data obtainable online [1]. Stocking, controlling, obtaining, and treating this large quantity of information constitute a vital requirement and a gigantic defy with a view to meet the expectation to discover, examine, extract, and envisage these data as information. This flood of data, in conjunction with rising methods and engineering employed to manage it, is frequently mentioned nowadays as Big Data computing [1, 6]. Big Data may be described as bulks of data obtainable in changing levels of intricacy, produced at various rates and changing levels of confusion, that cannot be treated employing conventional engineering, treating techniques, algorithms, or any commercial off-the-shelf solutions [7, 8].
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