Decision making in the economy demands tools to find the most effective, cost-affordable and optimal solutions. Besides, there is a high necessity to have possible solutions not for tactic needs but for strategic as well. Business and economic analysts of all levels economic management are eager to put up the user-friendly software, apps or solutions to support their analytic and forecasting attempts. In the epoch of the claimed Industry 4.0, rapid digitization and on-line of recent quarantine events, the information systems and any computer support is the best possibility and treasure. This paper is devoted to the idea of possible computer support for the analysis and forecasting of economic dynamics. The particular attention is paid to the time series modelling and detecting of its cyclic component. The majority of economic time series have the seasonality or other cycling inside of its dynamics, that could dramatically pervert the linear trend forecast or any other determinate direction of the trend. The proposed information system is quite user-friendly but the low error way provides a potential user with the tool of cyclic component forecasting. The methodology is grounded in the Assimakopouloscyclicity filter. The case of Denmark GDP quarterly since 1995is presented to test and confirm the system effectiveness in acquiring knowledge about the dynamics of the economic system. The sufficient accuracy of the implemented forecasting methods is presented.