Building Data-Driven Organizations: A Theoretical Exploration of the Role of leadership in Big Data Management

Abstract

Problem: The adoption of Big Data and business intelligence is often limited by the lack of leadership with the necessary skills to manage the information provided by the data. This is compounded by the absence of an organization with an established data-driven culture. Objective: The objective of this study is to analyze how the role of leadership influences the development of a data-driven organizational culture and how this relates to Big Data management. Methodology: A mixed-methods approach was used, based on a systematic literature review of high-impact databases such as Scopus and Web of Science regarding leadership, organizational culture, Big Data, data culture, and decision-making processes published between 2015 and 2025. Results: The study identified four key drivers: data analysis, data democratization, data-driven leadership, and ethics in data-driven decision-making. Conclusions: The study confirms that data analytics, information democratization, data-driven leadership, and a data culture are essential pillars for moving toward truly evidence-based organizations. The coherent integration of these four drivers enables organizations to address the challenges arising from informational complexity and fosters more responsible, ethical, and strategic decision-making. However, it is acknowledged that consolidating this approach requires leadership capable of guiding cultural transformation and mitigating the risks associated with data overload, which defines the scope of this study and opens opportunities for future research