The article analyzes different approaches to design adaptive educational systems on the basis of students' learning style identification. As a result of the investigation a system to identify the student's learning style with the data analyzing module has been designed and implemented. A data analyzing module is applied for the further adaptation of digital educational content and educational methods to students' learning style. The data background for the module to analyze learning style identification system is the universal e-learn environment users’ database, the results of learning style identification due to ВАРК model or any open external information like psychotype, type of intelligence, etc. Data storage uses the concept of data warehousing to predict special methods for data model design taking into account the integrity of datasets from different sources, object orientation, consistency, data consolidation or multidimensional data architecture to simplify analytical queries. The data analyzing technologies being applied within the system are based on the information retrieval approach using languages of SQL; OLAP and Data Mining technologies. The results of the system implementation gave an opportunity to fix the correlation of learning styles with other personal characteristics like psychotype, gender, secondary education level, academic achievements, etc. The represented data of data analysis concerning IT major students give reason for the conclusion about the necessity to adapt digital content to multimodal and kinesthetic learning style, to apply learning methods and technologies on the basis of project tasks, group communication and collaboration.