Introduction
In the digital age, data is often regarded as the most valuable commodity, akin to oil in the previous century. However, like oil, data requires refining to unlock its full potential. This article explores the concept of reusable data, emphasizing its importance in driving analytics and artificial intelligence (AI) applications. Reusable data is characterized by its consistency, self-explanatory nature, and ease of access, aligning with the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. The article outlines a step-by-step approach to making data reusable, including identifying data silos, transferring data to a unified storage location, harmonizing data structures, and ensuring data integrity. By adopting these practices, organizations can transform raw data into valuable assets that fuel innovation and strategic insights.