Data mining is an integral part of BI. It is the process of identifying useful and understandable patterns in data, or discovering useful information through data mining tools that put the obtained information into practical use. A well conducted analysis can be of strategic importance to an organisation because by uncovering the right information from data, informed decisions are made and competitive advantage can be achieved in the market. The European Union, a regional organisation of European states and the only organisation of its kind in the world, is no exception. It provides funding for a range of projects and programmes to achieve the objectives of cohesion policy in the territory of the Member States. Financial resources shall be disbursed from the ESI Funds in accordance with the specific programmes and their priority objectives. In Croatia, these are the OP ‘Competitiveness and Cohesion 2014.-2020’ and the OP ‘Effective Human Resources 2014.-2020.’ whose datasets on funded projects for the implementation of cohesion policy, implemented at local and regional level, provide the basis for the implementation of data mining techniques in this research. The research shall be based on the applicability of data mining methods and techniques on selected datasets which are publicly available on the websites of the European Structural and Investment Funds. Therefore, in research a theoretical data mining term, concepts and techniques are elaborated and an analysis of disbursed ESIF funds to the member states of the European Union in the financial perspective of 2014.-2020. was given. Furthermore, it describes the cohesion policy in Croatia which includes the funds from which projects are financed, the Operational Programmes, the NUTS distribution of regions in Croatia into Adriatic and Continental Croatia where according to a certain number of inhabitants a certain amount of financial resources is made available for the development of each region. In the empirical part of the research, the Microsoft Power BI tool performs a data visualization and further analysis of the data set by selected data mining techniques allows to gain insight into the relationships, logic, regularity or any structure between the data. In addition, the applicability of the data mining tool on the selected data set was presented and conclusions were drawn on the projects intended for the implementation of the cohesion policy financed from the ESI funds. The obtained information about the allocated funds and the distribution of the allocation to projects according to certain attributes from the ESI funds by researching the variables of the selected dana set can be used to improve decision making to current and future beneficiaries of EU grants and to all those who find this research useful.