A COMPARATIVE STUDY OF BIG DATA PLATFORMS AND CLOUD COMPUTING PLATFORMS: EVALUATING SCALABILITY, SECURITY, AND ANALYTICAL CAPABILITIES

Abstract

The rapid growth of digital technologies and data-driven decision-making has significantly increased the importance of efficient data processing platforms. Organizations across industries generate massive volumes of structured and unstructured data that require advanced systems for storage, management, and analysis. Big Data platforms and Cloud Computing platforms have emerged as two prominent technological solutions that support large-scale data processing and analytics. While Big Data platforms are designed specifically to handle large and complex datasets through distributed computing frameworks, Cloud Computing platforms provide flexible and scalable infrastructure that enables organizations to store, process, and access data remotely. This study presents a comparative analysis of Big Data platforms and Cloud Computing platforms with a focus on their scalability, security mechanisms, and analytical capabilities. The research examines how these platforms support organizations in managing high-volume data environments and enabling advanced analytics for informed decision-making. Furthermore, the study evaluates the adaptability of these platforms in handling large-scale data processing tasks across different business contexts. By identifying the strengths and limitations of each platform, the paper aims to provide insights that can assist organizations in selecting the most suitable technological framework for their data analytics requirements. The findings contribute to a better understanding of how modern enterprises can leverage data platforms to enhance operational efficiency, innovation, and strategic planning.