Building of modern enterprise information systems

The paper presents an analysis of modern approaches and practices that are used in the building of enterprise information systems. The problems of the isolation of practice from theoretical research are revealed. The main characteristics of big data, solutions for storing enterprise information, the applicability of machine learning, its tools and relevance in modern conditions are considered. Among other things, such necessary aspects of development of information systems as reliability, scalability, maintainability and safety are considered. As a rule, existing systems store only the current state. The event flow is proposed as a method of storing, processing and presenting data for management decision-making in conditions of instability, which is relevant to the current business needs. The reasons behind the complexity of the transition to the flow of events as a storage system are revealed. In light of the changing set of used technologies and the new focus on data analysis, the basic labor market requirements for specialists at the intersection of programming and data science are being laid down. The main skills and market requirements include work at the intersection of several areas, expertise in deploying applications in cloud services, writing clean code, knowledge of mathematical apparatus at the level necessary for rational use of machine learning models, as well as competent ability to build parallel processing in several streams. The main competitive advantages of business are flexibility and the ability to get the most out of information.