The labor market evolution highlights data literacy as vital for future graduates, not just as a skill but as a cornerstone for resource efficiency and data-driven decision-making. This study explores instructional methods going beyond traditional coding-centric approaches, to enhance data literacy for non-STEM business students. It supports National Academies’ and supranational organizations’ push for specialized data education across academic and corporate domains. Three key teaching approaches are detailed: coding approaches using Phyton, R, etc., data-centric tools like Microsoft Excel, and visualization-based techniques (Power BI, Tableau), evaluating their strengths, challenges, and applicability across fields. In a pilot case study, an innovative “Data Literacy” module within an MBA program is presented and detailed. This module, embracing technical, methodological, and application-related aspects, intends to equip business students with versatile skills for data-centric environments. The paper concludes by stressing the need for ongoing improvement in data literacy teaching modules to business students in higher education institutions, considering their positive impact in real-world settings. The success of these practical modules among business students signifies the promising integration of data literacy into professional curricula, preparing graduates more effectively for tomorrow’s data-driven workplaces.