The burgeoning growth of data, estimated at a 20% annual rate, is compelling organizations to evaluate their data management approaches, weighing the tradeoffs between centralized and decentralized models. Centralized systems, using data warehouses or lakehouses, offer efficiency and consistency by avoiding data replication, but they pose privacy risks, limit user control and innovation, and create "walled gardens" where data portability is restricted. In contrast, decentralized data management, favored for its scalability and reliability, empowers stakeholders with greater autonomy and innovation potential by allowing them to directly manage and enhance their data. However, decentralization introduces challenges such as ensuring data consistency across multiple locations and managing increased attack surfaces. Decentralized systems benefit from technologies like distributed ledger technology, encryption, decentralized identifiers, and smart contracts to maintain security and facilitate data interoperability. This model, exemplified by companies like Netflix and Amazon, is gaining favor as it supports agility, innovation, and redundancy, with APIs serving as the crucial conduit for data flow, facilitated by platforms such as Kong Gateway and Kong Mesh.