International Journal of Science, Engineering and TechnologyAuthors: Abhendra Pratap Singh, Kanika, Nehal Sharma, Nandini Sharma
Abstract: In today’s era, data is the most important element, and data generation is increasing day by day. Due to this increase in data, traditional servers cannot handle large amounts of information efficiently. Therefore, the present generation requires more advanced server infrastructure. In traditional systems, limited storage, low processing speed and lack of scalability are common issues. In big data systems, the 3V model (Volume, Velocity, Variety) is followed. Big data analytics server machines have high-performance processors. They also include parallel processing support, distributed architecture and cluster-based systems. The main role includes on-demand resources, virtualization, resource pooling and elastic scalability. Therefore, big data analytics server machines are a fundamental component of modern computing environments. Big data analytics plays a vital role in server machines and serves as a fundamental component of modern computing environments. This paper represents how this technology has transformed. This paper discusses big data features such as volume, velocity, and variety, along with evolving technologies such as Apache Hadoop, MapReduce, Spark, SaaS, PaaS, and IaaS. It also explains the differences between big data analytics, big data storage, and big data warehousing. Furthermore, it discusses cloud computing and software such as Kafka and its importance in cybersecurity. Security is a crucial component of cloud-based big data analytics, as it protects sensitive data. Cloud companies ensure protection through data encryption, access control, and compliance with security standards.
DOI: http://doi.org/10.5281/zenodo.21719710
