The Application of Big Data in Enterprise Information Intelligent Decision-Making

Abstract

With the continuous increase of mass information in the process of enterprise operation, information redundancy interference poses a challenge to enterprise information decision-making. Therefore, this paper applies big data analysis technology to enterprise information intelligent decision-making, and builds an enterprise information intelligent decision-making model based on big data analysis. The key data of enterprise is mined by using the density weight Canopy to improve the K-Gmedoids algorithm. After sorting, filtering, and transforming, the big data model designed in this paper uses interactive genetic algorithms to obtain the optimal decision-making strategy of enterprise information through experimental tests, which has a significant impact on the decision-making management and the competitiveness of the enterprise. In the process of enterprise information collection and intelligent decision-making, the interactive genetic algorithm generates a 95% match between the optimal business operation plan and the problems that need to be solved in the actual operation of the enterprise, which can better improve the ability of the enterprise to deal with problems. The number of iterations of the optimal decision-making plan obtained by the company is only 6 times, which has a good use effect while improving work efficiency.