This chapter delves into the future development direction of e-commerce big data, analyzing and exploring the four areas of data fusion, data mining, data security, and application prospects. In the data fusion section, this chapter focuses on how to improve e-commerce enterprises’ insights into the market and customers by integrating multi-source and multimodal data, so as to provide more accurate and personalized services. Achieving a unified representation of multimodal data is the key to reach this goal. In the data mining aspect section, this chapter explores the fact that with the continuous advancement of AI technologies, the mining capability of e-commerce big data has been significantly improved. These advanced technologies and algorithms provide a strong support for platforms to efficiently mine the potential value in data and optimize the decision-making process. Regarding the data security section, this chapter provides an in-depth analysis of the security challenges faced by e-commerce big data in terms of storage, sharing, and ownership. Given that e-commerce platforms involve a large amount of users’ personal information and business data, ensuring the secure storage and compliant use of such data has become a key task in protecting users’ privacy and maintaining business secrets. For the “Application Prospects” section, this chapter looks at the broad application potential of e-commerce big data in the future, covering innovation and development in areas such as risk management, intelligent logistics, and intelligent marketing. Through the scientific application of big data technology, enterprises will not only be able to optimize their operational processes and enhance their market competitiveness but will also play a positive role in promoting the sustainable development of the economy and society.