Intelligent decision-making based on data analysis is of great significance to enhance the competitiveness of enterprises. Querying and obtaining the information and complete data closely related to the problem from the internal information system database, is a key point in enterprise data analysis. The ontology-based visual query system (VQS) provides end-users with an effective way to access data. In recent years, by using the simple mapping rules, the database table, field, the foreign key relations, and other elements is directly mapped to the concept, attributes, and relationships in the ontology. It exposed too much database design technical details to the end user, thus increasing the end users' burden when using the VQS system. Masking database details by manually writing mapping rules is both inefficient and not universal. To this end, this study proposes a reasoning-based end user ontology query construction method. This method uses the semantic expression ability and reasoning ability of the ontology model to inject the domain knowledge into the original ontology model that is directly derived from the database. It optimizes the query construction process and enables the end user to query and manipulate the data from the domain experts' perspective, instead of a database design perspective, which improves system usability. It adds support of the group statistics and extends the application scope of the method. Finally, this method is evaluated by analyzing real cases in the field of "Restaurant Information Management" and the experimental results demonstrate that the proposed approach outperforms other baseline methods. the proposed approach has improved the usability by 53.44% and the expression ability by 20.43%.