System for Analytical Processing with an Integrated Data Warehouse for Presenting Tourism Trends: (Case study: Sarajevo)
This paper presents a methodological approach for integrating heterogeneous tourism data into a unified spatiotemporal analytical framework. By combining business intelligence, geospatial processing, and machine learning techniques, the proposed system enables a predictive and spatially aware analysis of tourist behavior. The approach is evaluated through a case study from Sarajevo Canton and demonstrates how fragmented data sources, temporal, spatial, and behavioral, can be semantically aligned to support strategic decision-making in tourism. Although the accuracy of the predictive model is constrained by data limitations, the integrated architecture reveals patterns in tourist flows and spatial clustering that are not captured by traditional methods. The main contribution lies in establishing a generalizable analytical approach to tourism intelligence, bridging data silos, and improving the analytical capabilities of destination management systems.