Enterprise Digital Retail Business Data Analysis and Forecasting Based on Time Series Analysis

Digital enterprise management refers to the use of digital technology and information systems to manage various businesses and processes of an enterprise in order to improve its efficiency and competitiveness. Digital enterprise management is crucial to the development and operation of enterprises, which can help them realize more efficient production and management, improve their efficiency and competitiveness, as well as improve their innovation and flexibility, so that they can be more adaptive to market changes and customer needs. This paper focuses on the significance and methods of time series analysis of a retail enterprise's sales. By analyzing the historical sales data, we can predict the future sales trend and change rule, formulate corresponding sales strategies and plans, and improve sales efficiency and profit. Time series analysis is a commonly used data analysis method, in which AR model, MA model and ARMA model are three commonly used models, which have different principles and applications.AR model is a model based on the historical data of the time series itself for forecasting, which assumes that the future values are only related to the past values.MA model is a model based on the historical data of the error term of the time series for forecasting, which assumes that the future values are only related to the past values. The ARMA model is a combination of the AR model and the MA model, which can take into account both the autocorrelation of the time series and the correlation of the error term. By comparing the performance of the three models, the most suitable model can be selected for forecasting. For retail companies, sales are a very important indicator. Through time series analysis, it is possible to understand the seasonal and cyclical pattern of sales, predict the future sales trend and change pattern, adjust the product structure, inventory management and marketing strategy in time, and improve sales efficiency and profit. In addition, it can also understand the development trend and potential of the enterprise by comparing the sales of different time periods, which can provide support and reference for the strategic decision-making of the enterprise.