Visualizing the Future: Integrating Data Science and AI for Impactful Analysis
DOI:
https://doi.org/10.63282/3050-922X.IJERET-V5I1P107Keywords:
Data visualization, Data science, Artificial Intelligence (AI), Machine learning, Predictive analytics, Impactful analysis, Data-driven insights, Big data analytics, AI integration, Decision intelligenceAbstract
The intersection of data science and artificial intelligence (AI) has not only transformed the value of data-driven decision-making but also enabled organizations to utilize data on a scale and variety that is difficult to mistake. The proposed study involves implementing a multidimensional framework to facilitate cross-domain, effective analysis by integrating AI-powered modeling with state-of-the-art data visualization techniques. The cross-domain integration of various open-source datasets, such as economic, healthcare, environmental, technological, and educational indicators retrieved primarily through the World Bank, Kaggle, and the World Health Organization, is an illustration of how cross-domain integration facilitates interpretation and strengthens evidence-based policymaking. The approach combines data exploration with predictive modeling and clustering algorithms in its interactive visualization tools, thus enabling both technical knowledge and stakeholder accessibility. It is found that the AI-based visual analytics have the ability to discover actionable patterns, detect anomalies, and produce interpretable outputs that are flexible in various industries. Combining the analytical sophistication of AI and the communicative sophistication of visualization, this work highlights the possibilities of composite frameworks in enabling informed, strategic, and future-minded decision-makin
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