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@article{176845,
        author = {Abu Hamza and Inzmam Ahmad and Yousuf Raja},
        title = {Cloud Based Big Data Analytics Platform},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {6179-6183},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=176845},
        abstract = {This project presents a cloud-based data analytics platform designed to process and analyze real-time streaming data using modern web and backend technologies [1]. The platform utilizes ReactJS for frontend interfaces, Node.js for backend services, Apache Kafka for high-throughput data ingestion, Redis for caching, and Elasticsearch for search and analytics capabilities [2]. The system is containerized using Docker and orchestrated with Docker Compose [3]. This architecture enables rapid, scalable, and reliable processing of data across diverse industry use cases such as logistics, finance, healthcare, manufacturing, and retail. The report details the design, implementation, challenges, and future improvements of the platform [4]. In the era of big data, real-time analytics has become a necessity across various industries [5]. This project focuses on designing and implementing a scalable, cloud-based data analytics platform leveraging modern web and data technologies [6]. The platform uses ReactJS for building an interactive frontend, Node.js as the backend runtime environment, Apache Kafka for data streaming, Docker for containerization, Redis for caching, and Elasticsearch for high-performance search capabilities [7]. The system is designed to handle high-throughput data streams, support real-time analytics, and ensure fault-tolerance and scalability via Docker-based orchestration [8]. This report explores the architecture, components, implementation challenges, and industry use cases, with a particular focus on resolving common data streaming issues in Apache Kafka [9].},
        keywords = {ReactJS, Node.js, Apache Kafka, Docker, Redis for caching, Elasticsearch for search capabilities, industry applications, data streaming issues with Kafka, and container orchestration with Docker.},
        month = {April},
        }