Cross-Disciplinary Approaches: The Role of Data Science in Developing AI-Driven Solutions for Business Intelligence
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Abstract
In today's data-driven world, businesses increasingly rely on artificial intelligence (AI) and data science to enhance decision-making processes and gain a competitive edge. This paper explores the cross-disciplinary approaches that leverage data science techniques to develop AI-driven solutions for business intelligence (BI). By integrating statistical analysis, machine learning, and data visualization, organizations can transform raw data into actionable insights. This study highlights the importance of collaboration between data scientists, business analysts, and domain experts to create robust BI systems. Furthermore, we examine real-world case studies that demonstrate the successful implementation of AI-driven BI solutions, underscoring the transformative potential of data science in various industries.
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