Research on the Design of a Sales Forecasting System Based on Hadoop Big Data Analysis

With the rapid development of big data technology, the demand for accuracy in sales forecasting by enterprises has significantly increased. This study designs and implements an efficient sales forecasting system based on the Hadoop big data analysis platform. By deeply exploring the integration of big data analysis techniques with sales forecasting models, this research proposes forecasting algorithms suitable for large-scale data processing and achieves parallel processing of these algorithms using the MapReduce framework within the Hadoop ecosystem. The system architecture includes multiple modules, such as the data layer, model layer, and application layer, aiming to meet the needs for real-time processing, scalability, and accuracy. Through experimental comparisons, this study evaluates the performance of different algorithms in handling large-scale data and ultimately determines the optimal sales forecasting solution. The results show that the system demonstrates high forecasting accuracy and processing efficiency in practical applications, providing strong support for enterprise sales decisions.