Personalization at Scale: Big Data Technologies in Digital Content Delivery and Their Effect on Viewer Experience

Ramalingeshwar Sirigade

doi:10.32628/CSEIT241051076

Authors

Ramalingeshwar Sirigade DIRECTV, USA Author

DOI:

https://doi.org/10.32628/CSEIT241051076

Keywords:

Big Data Analytics, Digital Content Delivery, Video Streaming Services, Customer Experience Optimization, Personalized Recommendations

Abstract

This article examines the transformative impact of big data technologies on the digital content delivery industry, focusing on their application in enhancing customer experience through video streaming services. Through a comprehensive case study of a leading provider, we investigate the implementation of Hadoop and AWS Big Data product suites to optimize content delivery, personalize user recommendations, and enable dynamic ad insertion. Our findings demonstrate significant improvements in service reliability, viewer engagement, and advertising effectiveness. The article reveals how Big Data analytics facilitate real-time content optimization and personalized user experiences, increasing viewer retention and satisfaction. Furthermore, we explore the challenges and limitations encountered during implementation, providing insights into the practical applications of Big Data in the evolving landscape of digital media consumption. This article contributes to the growing body of literature on Big Data applications in media and entertainment, offering valuable insights for practitioners and researchers in digital content delivery.

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