Recent years have seen digital technologies become integrated into traditional educational systems. This integration has facilitated access to a vast amount of educational data, ranging from the aggregation of learning outcomes to the prediction of student behaviour within e-learning courses. Many universities, both in Ukraine and around the world, have adopted the open learning management system (LMS) Moodle for e-learning. In addition to serving as a platform for delivering educational content, Moodle encourages active student engagement through a variety of activities, including quizzes, assignments, and forum-based communication. Through these activities, students create a digital footprint which, when analysed, can be used for management purposes. Modern learning analytics methods enable the identification of behavioural patterns within the data generated by participants in the educational process. These analytics facilitate the construction of individualised learning pathways and the application of newly gained insights to improve the overall quality of the educational process. This paper highlights the range of data analytics technologies applicable to the design of various digital learning environment systems. Particular emphasis is placed on the creation of a system dedicated to the analysis of big data in the context of Moodle distance learning. The paper describes and explains a set of data analysis tools specifically tailored for Moodle LMS courses. Using Moodle’s standard analytics capabilities alongside other relevant tools, an experimental study was conducted, exemplified by the analysis of a specific educational portal within a higher education institution. This empirical investigation aimed to demonstrate the practical application of data analytics technologies in the context of a specific e-learning environment, and to highlight the potential benefits and implications for educational institutions embarking on digital transformation.