Data science represents a paradigm shift in the education sector, enabling the transformation of vast amounts of data generated from educational processes into deep, actionable insights. By analyzing student learning patterns, curriculum performance, and teacher interactions, data science provides an unprecedented understanding of the factors influencing academic achievement. For instance, predictive analytics can help identify students at risk of falling behind or dropping out early, allowing for precise and timely interventions. It can also be used to design personalized learning pathways that adapt to each learner's pace and comprehension, and to refine educational content based on identified strengths and weaknesses. At the administrative level, data analysis assists in evaluating the effectiveness of educational policies and optimizing resource allocation. In essence, data science transforms education from a generalized system treating students as a homogeneous group into an intelligent, individual-focused ecosystem. It enhances overall quality through evidence-based, analytical decision-making, ultimately fostering a more equitable and effective learning environment.