Think big. Learning contexts, algorithms and data science

Due to the increasing data growth available in recent years, all areas of research and the management of institutions and organizations, and specifically in schools and universities feel the need to give meaning to this availability of data. This article after a brief reference to the definition of big data, intends to focus attention and reflection on their type in order to proceed to an extension of their characterization. One of the hubs to make feasible the use of Big Data in operational contexts is to give a theoretical basis to which to refer. The DIKW model (Data, Information, Knowledge, Wisdom) correlates these four aspects concluding in Data Science which in many ways could revolutionize the established pattern of scientific investigation The Learning Analytics applications on online learning platforms can be tools for evaluating the quality of teaching. And that's where some problems arise. It becomes necessary to handle with care the available data. Finally, a criterion for deciding whether it makes sense to think of an analysis based on Big Data can be to think about the interpretability and relevance in relation to both institutional and personal processes.