This paper aims to address the complex challenges associated with managing knowledge in the context of financial market data analytics. It presents a novel software architecture that makes use of a knowledge graph for building and executing analytics processes. It describes how the different architectural components interact with each other to fulfil the needs of the user(s). The proposed solution is validated by developing a software prototype and testing it on a scenario involving the computing of a financial market measure. This approach underscores the potential of integrating knowledge management practices into analytical environments, especially in handling the complexity and variability of financial market data analytics processes.