###### Abstract  
Currently, data are a very valuable resource for organizations. Through analysis, it is possible to profile people or obtain knowledge about an event or environment and make decisions that help improve their quality of life. This concept takes on greater value in the current pandemic, due to coronavirus disease 2019 (COVID-19), that affects society. This emergency has changed the way people live. As a result, the majority of activities are carried out using the internet, virtually or online. Education is not far behind and has seen the web as the most successful option to continue with its activities. The use of any computer application generates a large volume of data that can be analyzed by a big data architecture in order to obtain knowledge from its students and use it to improve educational processes. The big data, when included as a tool for adaptive learning, allow the analysis of a large volume of data to offer an educational model based on personalized education. In this work, the analysis of educational data through a big data architecture is proposed to generate learning based on meeting the needs of students. adaptive learning; big data; online education +
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Transforming the time that a person dedicates to each activity into effective time is the problem that several scientific studies face. Universities and their educational models are the ideal environments to propose techniques or models that focus on the effective development of people [10]. Current educational models, such as the online study modality or face-to-face models, include ITs in all their processes to improve them and learn from possible mistakes [11]. However, in practice, the inclusion of IT has not solved problems such as dropouts or low academic effectiveness; in certain circumstances these problems have even been increasing. In response to these events, universities have taken steps to include student-based learning techniques, such as problem-solving-based learning, flipped learning, project-based learning, etc. These techniques are part of a very powerful model such as adaptive or personalized learning [12]. This type of learning places the student as the main actor in their education, for which IT is used as a main tool [13]. The concept of adaptive learning is aligned with the new reality that society is currently experiencing. Being affected by the Coronavirus Disease 2019 (COVID-19) pandemic, universities were involved in serious problems [14]. The continuity of education the same as most activities was stopped by a mandatory quarantine. A part of the solution to face the chaos generated came from information and communication technologies (ICTs) with teleworking and the use of different applications that allow synchronous communication. The effect of COVID-19 on education had serious implications that will be reflected in the periods after 2020. Although the face-to-face models went to a virtual or online mode and continued with their activities, the change was so abrupt that both resources and learning activities designed in a face-to-face education model were not adjusted to the new needs of the students. With this precedent, it is necessary to promptly update the educational models designed for adaptive learning where the entire academic environment revolves around the student [15]. In this work a data analysis model based on the use of a big data framework is proposed [16]. This model allows the processing of the large volumes of data that students generate in their academic activities and analyzes them to obtain knowledge about their needs [17]. With this information, it is possible to determine exactly what problems students present, for this it will be necessary to identify the different patterns in the data and classify individuals in order to offer an adaptive learning model.