
A Cutting-Edge Method on Big Data Analytics Recent Developments for Business Operations and Security Management
Citation: Razzhivin, O.A., Ollanazarov, B.D., Okagbue, H.I., Andryushchenko, I.E. (2025). A Cutting-Edge Method on Big Data Analytics Recent Developments for Business Operations and Security Management. In: Simic, M., Bhateja, V., Azar, A.T., Lydia, E.L. (eds) Smart Computing Paradigms: Advanced Data Mining and Analytics. SCI 2024. Lecture Notes in Networks and Systems, vol 1262. Springer, Singapore. https://doi.org/10.1007/978-981-96-1981-8_18
Abstract
The management of a corporation could be significantly enhanced by the use of big data. There has not been enough statistical investigation to determine the importance of large data in the malignancy of the highly functional and methodical investigations. Extremely massive data compilations featuring a more intricate and diversified structure are referred to as big data. These traits usually lead to more challenges when it comes to data extraction, analysis, storing, and further operations. “Big data analytics” is the process of examining enormous volumes of complicated information to uncover hidden patterns or connections. However, there is an obvious conflict between the expanding usage of big data as well as its safety and confidentiality. It addresses the most crucial elements of computer network management and organization, including privacy, in order to meet the demanding security standards of big data applications. Since more and more individuals share personal data and materials on social networks as well as public cloud services via their PCs and smartphones, it is crucial to find a solution to this problem. Consequently, creating a secure foundation for social networks has become a hot research subject. One of each of the case study sections in this chapter deals with this last subject. In addition, Big Data computing systems are not appropriate for the use of conventional security measures like firewalls and demilitarized areas. But if information is not sufficiently protected against threats like phishing and hacking. These difficulties include vulnerabilities in open databases; safeguards against hacking and data leakage; and so on. When managing large-scale, dispersed data sets, safeguarding and privacy requirements provide a serious challenge to monitoring and tracking data use and access in a dynamic, distributed context. This effort aims to investigate the issues that arise in attempting to maintain the security and privacy of large amounts of data, and also to identify solutions for these issues.