Research on Business Intelligence Based on Adaptive Algorithm

Business intelligence represents a sophisticated stage of enterprise informatization, with a primary objective of transforming business data into valuable knowledge and providing decision-making support for enterprise managers. This ultimately serves to enhance the competitive advantage of enterprises. The application of modern information technology enables business intelligence to efficiently collect and manage both structured and unstructured data. Adaptive algorithms are designed to identify changes in data patterns by monitoring and analysing business data in real time. They are capable of dynamically adjusting data analysis processes and strategies based on these changes, thus ensuring the most up-to-date and relevant results. This dynamic adjustment not only enhances the efficiency of data processing, but also guarantees that the results of the analysis are consistently pertinent to the prevailing business environment. The proposed model is based on machine learning technology, which is used to continuously optimise the performance of the analysis algorithm through an iterative training and feedback mechanism. This allows the algorithm to become more adaptable in a variety of business scenarios. The results of the experimental analysis demonstrate that, in comparison with traditional business intelligence methods, the adaptive method exhibits a notable enhancement in prediction accuracy and decision support quality.