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Research on the Application of Data Mining in Income Forecast: An Empirical Business Analysis of Telecommunication Corporates

There exists a lot of valuable information with decision-making significance hidden behind the historical data. The methods of statistics and artificial prediction has been unable to well mine the useful information of telecom business decision-making. Therefore, this paper adopts MSSQL, .NET, Ajax and other related technical theories to complete the realization of the revenue forecast system. Firstly, the difficulties and challenges faced by telecom enterprises are analyzed, and the necessity of establishing business analysis system based on data warehouse is put forward. Then, based on in-depth study of data warehouse and business analysis system technology, the data warehouse model of enterprise business analysis system is analyzed in detail, and the grey prediction data of trained weight and threshold network is performed. Finally, through the comparison between the prediction results and the actual data, which model has the advantages of low cost is proposed. The selected model has higher accuracy. The application results show that the prediction accuracy of the combined forecasting model is higher than that of the previous methods, and the prediction results are more stable.