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@article{193867,
        author = {Anunitha .M.R and k. Gowri and R. Virshika and V. Kishore},
        title = {Cloud-Based Advanced Business Intelligence and Predictive Analytics Using Power BI},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {2181-2186},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193867},
        abstract = {The exponential growth of organizational data has increased the demand for intelligent systems capable of transforming raw data into actionable insights. Traditional on-premise business intelligence systems face challenges such as limited scalability, delayed reporting, and high infrastructure costs. Cloud computing has emerged as an effective solution to overcome these limitations by enabling flexible, scalable, and cost-efficient analytics platforms.
This research presents a cloud-based business intelligence framework integrated with predictive analytics using Microsoft Power BI. The proposed system leverages cloud-hosted datasets to generate interactive dashboards, real-time reports, and forecasting models that support data-driven decision-making. Predictive analytics techniques are applied to historical data to identify trends, patterns, and future outcomes. Experimental analysis demonstrates that the cloud-based Power BI solution improves reporting efficiency, scalability, and decision accuracy when compared with traditional BI systems. The study highlights the effectiveness of cloud BI platforms in supporting modern organizational analytics requirements.},
        keywords = {Cloud Computing, Business Intelligence, Power BI, Predictive Analytics, Data Visualization, Decision Support Systems, Cloud Analytics.},
        month = {March},
        }