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The exponential growth of data worldwide, fueled by the internet, smartphones, and social networks, has led to the emergence of big data-vast and complex datasets that typically range from a petabyte to an exabyte in size. Traditional database systems are inadequate for cap truing, storing, and analyzing such enormous amounts of data. Big data analytics enables businesses and governments to gain insights from unstructured data in unprecedented ways. With big data being a prominent and influential topic in the IT sector, its impact on various industries, including traffic management, banking, retail, education, and healthcare, is expected to be significant. In this research, we delve into the key concepts and challenges associated with big data. We explore the definition of big data and the criteria used to identify it. Additionally, we examine the steps involved in data processing and highlight the security features inherent to big data. To address these challenges, we present a novel framework called big data mobile analytics. This framework leverages big data profiles, access behaviors, and patterns to support offline and online activities, utilizing advanced analytics techniques to provide personalized advertising recommendations. Through this framework, we achieve enhanced security, efficiency, and accuracy in the analysis of big data. By seamlessly integrating multiple data sources and utilizing advanced analytics models, our framework enables organizations to unlock valuable insights, optimize decision-making processes, and enhance overall efficiency.

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Harnessing Fusion’s Potential: A State-of-the-Art Information Security Architecture to Create a Big Data Analytics Model

  • 会议论文

  • 发表日期：

    2025年

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  • Esther Jyothi Veerapaneni,
  • M. Ganesh Babu,
  • P. Sravanthi,
  • Pamidimukkala Sai Geetha,
  • Vahiduddin Shariff,
  • Swapna Donepudi

摘要

The exponential growth of data worldwide, fueled by the internet, smartphones, and social networks, has led to the emergence of big data-vast and complex datasets that typically range from a petabyte to an exabyte in size. Traditional database systems are inadequate for cap truing, storing, and analyzing such enormous amounts of data. Big data analytics enables businesses and governments to gain insights from unstructured data in unprecedented ways. With big data being a prominent and influential topic in the IT sector, its impact on various industries, including traffic management, banking, retail, education, and healthcare, is expected to be significant. In this research, we delve into the key concepts and challenges associated with big data. We explore the definition of big data and the criteria used to identify it. Additionally, we examine the steps involved in data processing and highlight the security features inherent to big data. To address these challenges, we present a novel framework called big data mobile analytics. This framework leverages big data profiles, access behaviors, and patterns to support offline and online activities, utilizing advanced analytics techniques to provide personalized advertising recommendations. Through this framework, we achieve enhanced security, efficiency, and accuracy in the analysis of big data. By seamlessly integrating multiple data sources and utilizing advanced analytics models, our framework enables organizations to unlock valuable insights, optimize decision-making processes, and enhance overall efficiency.