As educational institutions navigate an increasingly data-rich environment, the effective use of Business Intelligence (BI) has become critical for strategic planning and improving learning outcomes. Data visualization stands as a core component of BI, yet its application is often fragmented, creating a gap between high-level institutional analysis and direct pedagogical support. This paper provides a comprehensive qualitative review that bridges this divide by exploring the distinct and complementary roles of traditional data visualization platforms and emerging Artificial Intelligence (AI) tools in education. Through a thematic literature review and a detailed comparative analysis, this study clarifies how visualization tools primarily serve administrators and faculty in data analysis and decision-making, while AI-powered tools are geared toward direct student interaction, offering personalized tutoring and adaptive feedback. The findings demonstrate that AI implementation yields significant improvements across a spectrum of metrics, including academic performance, student engagement, and teacher efficiency. The paper concludes that a holistic, integrated data strategy—one that prioritizes visualization literacy, addresses systemic challenges, and leverages the unique strengths of both visualization and AI tools is essential for transforming raw data into meaningful insights and fostering a new generation of data-literate, ethically responsible citizens.