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Exploring Cloud Solutions for Real-Time Big Data Processing

Authors

Vandana Nemane

Department of Computer Science, Dr. D. Y. Patil Arts, Commerce and Science College, Pimpri, Pune, Maharashtra, India (IN)

Prajakta Patil

Department of Computer Science, Dr. D. Y. Patil Arts, Commerce and Science College, Pimpri, Pune, Maharashtra, India (IN)

Article Information

DOI: 10.51583/IJLTEMAS.2025.1413SP017

Subject Category: Computer Science

Volume/Issue: 14/13 | Page No: 76-79

Publication Timeline

Submitted: 2025-10-23

Published: 2025-10-23

Abstract

Abstract: Cloud-based solutions provide flexibility in storage and processing capabilities, allowing for tailored adjustments as organizational needs evolve. Collaboration is fostered, enabling data sharing and teamwork among diverse users and teams. Accessibility becomes universal, harnessing the potential of big data analytics from any location with an internet connection.  The period of big data has brought about unknown challenges and openings for data processing and analytics. The volume, haste, and variety of data generated bear scalable and effective processing results. Real- time, contextual, and secure data is now charge critical.data streaming platforms (DSPs) play a vital part in simplifying access to real- time data and making it easy to exercise whenever and wherever it’s demanded. This paper explores the concept of big data processing in the cloud and its significance in enabling real- time data analytics. By using cloud infrastructure, we can process huge amounts of data assisting real-time data analysis.


The paper delves into the benefits of cloud based big data processing, including elastic resource provisioning, cost optimization, and simplified data operation. Through this comprehensive analysis, the paper aims to exfoliate light on the eventuality of cloud computing in scalable and real- time big data analytics, empowering associations to decide precious perceptivity and make data- driven opinions.

Keywords

Big Data Processing, Cloud Computing, Real-time Data Analytics

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References

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