Educational technologies (Edtech) collect private and personal data from students. This is a growing trend in both new and already available Edtech. There are different stakeholders in the analysis of the collected students’ data. Teachers use educational analytics to enhance the learning environment, principals use academic analytics for decision making in the leadership of the educational institution and Edtech providers uses students’ data interactions to improve their services and tools. There are some issues in this new context. Edtech have been feeding their analytical algorithms from student’s data, both private and personal, even from minors. This draws a critical problem about data privacy fragility in Edtech. Moreover, this is a sensitive issue that generates fears and angst in the use of educational data analytics in Edtech, such as learning management systems (LMS). Current laws, regulations, policies, principles and good practices are not enough to prevent private data leakage, security breaches, misuses or trading. For instance, data privacy agreements in LMS are deterrent but not an ultimate solution due do not act in real time. There is a need for automated real-time law enforcement to avoid the fragility of data privacy. In this work, we take a step further in the automation of data privacy agreement in LMS. We expose which technology and architecture are suitable for data privacy agreement automation, a partial implementation of the design in Moodle and ongoing work.