Building a Resilient ODS Integrating Graph Algorithms and Azure for Enterprise Analytics

Abstract

The establishment of a contemporary Operational Data Store (ODS) design and architecture incorporates investment, financial, operational, and market-related datasets across various countries into one central repository at a multinational Private Equity Firm. The architecture incorporates an event-driven and graph-aware design methodology with a selective refresh approach for overcoming challenges related to very large datasets, multiple dependencies between financial indicators, and real-time updating and synching of data. By utilizing various Azure-native services paired with superior graph algorithms, the Platform offers more scalability around data management, better manages intelligent re-calculation capabilities, and provides near- real-time analytics. By offering a consolidated view in terms of corporate reporting this architecture has also significantly improved overall operational efficiency while simultaneously lowering costs and increasing the speed at which decisions can be made. Additionally, this research provides the groundwork for further developing automation and predictive analytic capabilities while emphasizing the value of creating innovative ODS designs that revolutionize the way in which financial/market-related data is managed.