The use of big data, called “oil of the 21^st century”, in public administration, in various spheres of the economy promises great prospects. This advanced technology has a great impact on improving public administration efficiency, quality and income in the economy. The fact that big data is a profitable industry and a high demand for it determines the formation and development of this industry as a special area of economic activity. However, since big data is a new and specific area of economic activity, there are a number of scientific and theoretical problems that need to be addressed. One of these problems is related to the functioning of the big data market. This article discusses some of the features and problems specific to the Big Data market. It identifies the unique features of data, which are the subject of the big data market, as economic assets and factors of production. The features of data are shown, which distinguish them from traditional economic assets and factors of production. Trading in the big data market has a number of unique characteristics and challenges. In research work, these features are classified and characterized. In particular, the issues such as trade in data of multiple owners, transparency, and fairness of trade, protection of confidentiality, data quality, and availability of Big Data are clarified. It also explains the pricing strategies, methods and pricing policies of companies in the Big Data market. The issues, such as the diversity of data sources, the complexity of data management, and differences in data are identified that make it difficult to determine such prices. The article also extensively discusses the competition, monopoly and opacity that are the main features of the Big Data market, and shows the factors that create these problems. In addition, the article analyzes and categorizes the issues that hinder the integrity of the global big data market. The study uses a systematic approach to economic research, comparative analysis, economic-composite and abstract-logical methods. The results obtained in the article can be used to solve scientific and theoretical problems of the Big Data market, as well as the formation and regulation of this market (pp.77-87).