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Relation between the identification processes of the enterprise state and the appropriate types of decision making Source: compiled by the author.
Source publication
The article is devoted to the development of a mechanism for the proactive support of strategic and operational decision-making in an enterprise. The starting point for this mechanism should be a model (pattern) of the enterprise, which embodies the principles of balanced strategic measurement systems. Development of the enterprise pattern as an ‘o...
Context in source publication
Context 1
... monitoring mechanism includes the formation of the enterprise pattern and its analysis as a first step. The further analysis of the formed pattern is associated with implementing the procedures of identification of the enterprise state with the subsequent conclusion on the necessity to change the objectives, strategies, and operative actions (Fig. ...
Citations
... Today, the external environment faced by management is changing rapidly. The intelligent make policy support systemic makes full use of the advantages of AI and expert systemic technology in qualitative analysis and uncertain reasoning and makes full use of human experience and knowledge in problem solving, thus providing a new way to solve practical problems [4]. This paper summarizes the research status of intelligent make policy support systemic and analyzes the challenges faced by IDSS and the further research direction. ...
With the development of message technology, big data is connected with business management. The research content and present situation of intelligent make policy support systemic in big data are introduced. Based on the knowledge-based systemic and its relationship with make policy-making process, the knowledge and knowledge processing systemic in IDSS are discussed. With the development of computer and its network, many enterprises have established their own message management systemics. How to observe the enterprise itself and the outside world in a flexible, real-time, vertical and horizontal, dynamic and slicing way, so as to capture relevant message for the development needs of the enterprise. The rapid development of big data has aroused widespread concern and attention at home and abroad. Scientific and effective analysis and processing of big data are the core issues in the field of big data. This paper summarizes the research status of big data analysis at home and abroad from three aspects: analysis as a service, big data analysis methods, and big data-driven science germination through literature review. By analyzing the statistical and semantic features of the existing data, we can find out the rules and then summarize them into an abstract data analysis model, thus providing the basis for data analysis, and the establishment of data graph and model can better reflect the specific content of the study. In the research of big data, it is found that both traditional data and big data have packet loss rates. According to the research, the packet loss rate of traditional data is as high as 70.9%, but that of big data is only 34.5%. Making a formula in the calculation of big data can help us to observe more. Through this research, it is found that big data has a more direct relationship with business management, and it controls various ways of enterprises. The era of big data has come, and all walks of life are faced with unprecedented data volume and data analysis requirements.
