The data revolution has opened up new possibilities for organizations to become more data driven and systematically make more informed and strategic choices. However, failing to transform the business to a data driven one remains a significant challenge for many organizations. In his book Data Driven Business Transformation Carruthers & Jackson described data driven business as a process that has a start and middle BUT no end. This research paper explores the state of the art in Data Driven organizations, examining theoretical frameworks from various sources to define a clear, working concept of data driven organizations for future research. We identified five key dimensions that distinguish data driven organizations from traditional counterparts. For a successful transformation, it is essential for data driven organizations to ensure access to high-quality data, establish a clear and well-defined strategy and architecture. Success in this transformation journey also hinges on fostering a data centric culture, building a robust infrastructure, and leveraging advanced analytical tools. Additionally, this research paper explores different use cases across industries, mainly in energy, finance and public sectors to assess the implication of Big Data & Artificial Intelligence and their impact on the organizations.