Data is becoming one of the most critical elements of competitive advantage, and this statement is becoming not just repeated regularly, but also increasingly evident. Naturally, companies want to benefit from this trend; it gives hope to gain business dominance. Unfortunately, merely few attempts end up successful.An example is the application of machine learning and artificial intelligence for business. Alongside advanced reporting and data visualization, these initiatives are enjoying increasing popularity; however, they are unworkable without adequate preparedness. In pursue of general trends, companies often end up with the outcomes different than initially expected. For example, the implementation of machine learning requires much more than just the "magic" code produced by a data scientist. In addition to the optimal model code, which is the primary focus of data scientists, there are many other aspects involved. I present the illustration from Google Research, that shows what other elements are required for merely technical implementation.My book is addressed to people interested in how to lead the organization towards the optimal use of data for business purposes; it presents the critical elements for achieving success. These aspects are discussed in four coherent, complementary chapters, each equally necessary, and all forming one whole. Those are: - business purpose and transition to business strategy, described in section one, - technology, its various aspects, and the arrangement of technological elements in a coherent architecture that meets business goals, often advanced technology, including unique algorithms, distributed processing, coming into areas from simple but necessary processing to topics of artificial intelligence, - data - the item from which we start, both big and small, instantly changing and the more static, structured, as well as those without a clear structure, raw, processed, incorrect, reference data and data characterized by numerous other features, - people forming teams, working in the organization and cooperating in different structures.The book is addressed to both policymakers, people that affect the organization's activities and strategic decisions, as well as those working operationally in various data-related processes. The book is also meant for analysts, architects, system designers, data scientists, administrators, users of analytical systems, and their managers. This is quite a significant group of people, and I believe it is continuously growing. The purpose is to help you see the elements that are not always easy to understand during regular work. These elements will be particularly essential in achieving success at various levels - personal, project, program and the entire organization.The unique role of "Chief Data Officer" is just newly emerging in many companies and is becoming essential in the structures of modern organizations. A job well done by CDO includes a broad perspective on many aspects of working with data and gives plenty of business value for the company. Individuals who practice it come from different positions and have diverse stories. Their role is continuously shaped by the market and has different purposes across companies and lines of businesses. However, projects, transformation programs and market changes conducted in numerous businesses allow to define it quite clearly. Being a CDO obliges to continuously learn and search for superior solutions, and that is what the book aims to arm the reader with - practical knowledge helpful on this challenging path.