Abstract
With the vigorous development of e-commerce, more and more goods are sold online. The electronic platform not only brings convenience to people's lives but also gives more people the opportunity of employment and entrepreneurship, which contributes to the promotion of economic value and the creation of wealth. With the gradual maturity of network technology represented by Big Data, it has also led to the further development of e-commerce. In the past, e-commerce mostly used business intelligence systems for data analysis. However, as the data becomes more and more complex, the innovation ability and data analysis ability of traditional business intelligence systems are relatively conservative, so it is of great significance to update and strengthen business intelligence to analyze its role in e-commerce data. Therefore, this paper proposed the application of business intelligence based on Big Data in e-commerce data analysis. By combining Big Data and a business intelligence system and taking the e-commerce data of a certain brand of beverage as the research object, the Days-Times-Money (DTM) model was established, and the data mining technology was used to classify the brand consumers. The data results showed that among the three consumption attributes, the highest consumption density of consumption days, consumption times, and consumption amount was 68.63 %, 67.99 %, and 69.72 % respectively. These were not more than 70 %, which indicated that the consumption of this brand of beverages had a high space for growth. According to the consumption density, the users of this brand of beverage were divided into four consumer groups. According to the classification results, it provided feasible marketing reference opinions for the brand beverage and could provide direction for brand value-added by mining the hidden data of the brand beverage. This paper hoped to use the brand beverage as a case to provide reference and reality for the development of e-commerce enterprises and provide a reference for the application and promotion of business intelligence based on Big Data in e-commerce data analysis.