Design of a Hadoop Based Data Platform for Auto Aftermarket

With the development of China's auto aftermarket, the share of auto aftermarket is going to increase in the future. Due to the unique characterizations of the auto aftermarket, dealers cannot provide adequate choices to customers due limitations in the venue or funds. Additionally, dealers cannot recommend suitable products to customers because the approach to determine their demands is relatively simplified. Moreover, it is complex to maintain the vehicles; therefore, a car owner is not able to make an appropriate maintenance plan and judge the quality of auto spare parts. The three problems bring high security risks. Through in-depth analysis of the status and prospects of the auto aftermarket, this study proposes and implements a Hadoop-based data platform using techniques of big data. The mentioned risks are reduced by the usage of cutting-edge technology for distributed systems and big data analysis techniques. The method can also provide a customized interface, which prepares for ongoing maintenance and the expansion of the platform.