The text outlines the process of using graphing techniques to analyze user login data for a social network application. It emphasizes the importance of tracking login times to optimize network usage and identify security issues. The process involves updating the 'loginTimes' attribute in user documents via an API endpoint and using a N1QL query to retrieve and organize this data for graphical representation. The data is grouped by time intervals, either by day or week, and visualized using Chart.js integrated with Angular.js for the front-end. The backend work involves generating an array of login counts indexed by time, ensuring that no undefined values disrupt the graphing process. The data is then sent to the client through an API endpoint, and the integration details with the front-end graphing library are documented in a GitHub repository. The tutorial concludes by inviting feedback and suggesting that the described method facilitates easier creation of charts using N1QL and a robust graphing library.