BIG DATA VS. CLOUD COMPUTING PLATFORMS: ASSESSING THEIR EFFECTIVENESS AND ADAPTABILITY FOR LARGE-SCALE DATA PROCESSING IN MODERN BUSINESSES

Abstract

The exponential growth of digital data has compelled modern businesses to adopt advanced technologies capable of handling large-scale data processing. Two major technological paradigms that address this challenge are Big Data platforms and Cloud Computing platforms. Big Data technologies enable organizations to process, analyze, and extract valuable insights from massive datasets, while Cloud Computing provides scalable infrastructure and on-demand resources for data storage and computation. This study examines the effectiveness, scalability, and adaptability of Big Data and Cloud Computing platforms in supporting large-scale data processing in modern business environments. It evaluates their architectural frameworks, performance capabilities, cost efficiency, and flexibility in handling dynamic data workloads. The paper also explores how the integration of these technologies enhances data analytics, decision-making, and operational efficiency. The findings suggest that while Big Data platforms specialize in managing complex data analytics tasks, Cloud Computing offers flexible and scalable infrastructure, making their combined adoption highly beneficial for modern enterprises seeking competitive advantages in data-driven decision-making.