Ethnic music has too many expectations due to its significance to the national culture. It serves as a mirror, reflecting all the true characteristics of many geographical areas and ethnic groupings. Instilling national self-confidence and fostering national unity are essential outcomes of this. The optimal design plan for Xinjiang folk music inheritance and environmental monitoring based on big data technology is presented in this study from the standpoint of cultural ecology. Big data technology can categorize users who are interested in Xinjiang ethnic music, and after that, through customized recommendation filtering, consumers may be presented with Xinjiang ethnic music that meets their interests. Last but not least, a simulation test and analysis are performed. The algorithm’s accuracy is 7.86% higher than that of the conventional algorithm, according to the simulation data. By studying and calculating the user’s behavioral traits and interests, this result demonstrates in detail how the recommender system can display the user’s content efficiently. However, there are numerous possibilities and varied contexts for the use of clustering techniques in recommender systems. It is crucially vital for directing the protection of ethnic music and fostering the inheritance and development of ethnic culture to conduct design study on the Xinjiang region’s ethnic music heritage and development with cultural ecology as the central guiding principle. This article is from “A comprehensive study of Uygur Muqam music art with Chinese characteristics,” which aims to improve the data reserve of the world and Southeast Asia on the research of Chinese Uighur Muqam art. Improve the inheritance and development of music in Xinjiang, China, and provide more detailed data to more scholars. This study adopts qualitative research methods and field survey data. The author proposes to focus on the perspective of cultural ecology, based on the use of big data technology, to improve the inheritance and development of Xinjiang national music.