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@article{194827,
        author = {Dr. R. John Mathew and D. Harsha Vardhini and K. Hyma Sri and A. Durga Maha Lakshmi and A. Aditya Subrahmanya Varma},
        title = {Best Streaming Service Analysis: Exploratory Data Analysis and Data Visualization},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {8067-8073},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194827},
        abstract = {Due to the competitive ecosystem created by the quick growth of digital streaming services, consumers now have to elect from a variety of platforms with a wide range of features and content libraries. This study compares the main OTT platforms using a data- driven logical frame that blends unsupervised machine literacy, visualization styles, and exploratory data analysis (EDA). To find patterns in happy vacuity, release trends, followership groups, and standing distributions, a dataset comprising movie- related attributes from top services like Netflix, Amazon Prime Video, Hulu, and Disney is examined. To guarantee logical delicacy, the dataset is pre reused using point metamorphosis, statistical confirmation, and cleaning. To probe platform-specific content distribution and standing geste, exploratory analysis is carried out. also, pictures are grouped using K- Means clustering according to parallels in release time, age group, conditions, and platform presence. The figure score is used to assess the quality of the clustering. An interactive web- grounded dashboard and relative visualizations are used to present the logical results. The findings show how statistical analysis and machine literacy ways support well- informed decision- making in the digital streaming ecosystem by offering structured perceptivity into platform specialization and content patterns.},
        keywords = {Data analytics, Data visualization, Exploratory Data Analysis, OTT platforms, Streaming services.},
        month = {March},
        }