The traditional education model gradually reveals the corresponding problems and deficiencies in the face of the update of the concept of education frontier and the change of talent cultivation mode. In this paper, we first sorted out the relevant features of the big data and data mining process, mined out the specific needs and realistic development dilemmas of musicology professional certification, and explored the appropriate mechanisms and strategies of UGS collaborative education and training. Using big data Hadoop technology as the infrastructure, a platform for music discipline services is designed to support interoperability and sharing of music education resources among universities, governments, and primary and secondary schools. Specifically, semantic similarity calculation is performed with music resource domain ontology to improve the intelligent retrieval ability, and the recommendation method of user dynamic preference is introduced to provide more accurate music teaching resources for platform users. The effect of cultivating musicology majors in colleges and universities is analyzed in terms of emotional attitudes, knowledge, and skills through the collaborative cultivation mechanism. The accuracy of the semantic similarity intelligent search method based on domain ontology is above 50%, and the mean value of students’ satisfaction with the intelligently recommended music learning resources is 4.3 points. 83.42% of the teaching carried out based on the subject service platform indicated that it met their learning needs, and the overall performance of the students who carried out the platform teaching was 16 points higher than that of the traditional classes. By using big data technology, the UGS collaborative cultivation mechanism can be utilized as a tool to enhance the quality of talent cultivation for musicology majors.