Dátová architektúra pre odvetvie finančných služieb

Big data applications in the financial services industry have been extensively researched, along with big data tools, but thorough sources of reference for big data architecture implementation in the industry are few and far between. The aim of this thesis is to review existing literature on data architecture for the financial services industry and design an architecture for data collection, processing, analysis, and presentation. The systematic literature review revealed research gaps, as only a small number of studies on the topic were identified. Additionally, the studies were heterogeneous and provided only high-level descriptions of data architectures. The research performed in this thesis was situated within the design-science paradigm, which seeks to develop new innovative artifacts. The requirements for the developed architecture were derived from several successful implementations in varying areas of the financial services industry. The resulting architecture combines a data lake with a data warehouse, separates the compute layer from the storage layer, and supports big data ingestion, storage, and processing.