Abstract

Innovative and sophisticated technologies have been rapidly developing in recent years. These cutting-edge advancements encompass a wide spectrum of devices like mobile phones, PCs and social media trackers. As a consequence of their widespread usage, these technologies have engendered the generation of vast volumes of unstructured data in diverse formats, spanning terabytes (TB) to petabytes (PB).This vast and varied data is called big data. It holds great promise for both public and private industries. Many organizations utilize big data to uncover useful insights, whether for marketing choices, monitoring specific actions, or identifying potential threats.This kind of data processing is made possible using different methods known as Big Data Analytics. It allows you to gain significant advantages by handling large amounts of unorganized, organized, and partially organized information quickly, which would be impossible with traditional database techniques. While big data presents considerable While it offers benefits for businesses and decision-makers, it also puts consumers at risk. This risk results from the use of analytics technologies, which need the preservation, administration, and thorough analysis of enormous volumes of data gathered from many sources. Consequently, individuals face the risk of their personal information being compromised as a result of the collection and revelation of behavioral data. Put simply, the excessive accumulation of data may lead to multiple breaches in security and privacy. Nevertheless, the realm of big data does indeed raise concerns pertaining to security and privacy. Scholars from various disciplines are actively engaged in addressing these concerns.The study will concentrate on large data applications, substantial security hurdles, and privacy concerns. We'll talk about potential methods for enhancing confidentiality and safety in problematic big data scenarios, and we'll also analyze present security practices

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