Due to the intensive development of information and communication technologies in the domain of production, large amounts of data are being generated. Many new approaches, methods, techniques, and tools for advanced data analytics are being developed and, consequently, additional possibilities of using large amounts of complex data - also referred to as big data, are emerging. However, the application of advanced data analytics in the production domain lags behind in penetration and diversity in comparison to other domains, and the data available often remains unexploited. This work presents the development and demonstrates the use of a framework for information support for processes in manufacturing systems. The framework is a conceptual tool that facilitates the introduction of big data analytics into manufacturing systems. The objective of the framework is to present a step-by-step procedure of introducing big data analytics into manufacturing systems and to systematically show what knowledge and skills, reference models, software and hardware tools, etc., are needed. The framework is based on the development and research of several data-analytics solutions developed during the course of this study, as well as on other existing applications and conceptual solutions from literature and practice. The feasibility and wide applicability of the framework at all manufacturing-system levels are demonstrated and validated.