Proceedings of the Technical University of Sofia

Abstract: Organizations operating within modern SAP (Systems, Applications and Products in Data Processing) landscapes are increasingly confronted with a range of complex challenges arising from the diverse and fragmented nature of enterprise data. This data originates from a variety of sources, including transactional systems, legacy databases and unstructured formats. The diversity of these sources creates major challenges in integration, scalability, data quality and regulatory compliance. Addressing these issues is essential to enable effective and sustainable decision-making processes. This work explores current advancements in SAP technologies, such as SAP Datasphere, SAP S/4 HANA and the SAP Business Technology Platform (BTP), which offer powerful capabilities for semantic integration, real-time analytics and enhanced automation. Following a review of recent studies and official SAP innovations, the analysis highlights the importance of continuous data quality management and modular governance structures. It also emphasizes the growing role of artificial intelligence (AI) and machine learning (ML) within decision intelligence frameworks.