A recent industry trend favors decentralized data architectures over the centralized data lakes and warehouses built for AI and analytics. This creates challenges, but also opportunities for data governance and data protection. In particular, data governance and data protection controls can be implemented in a federated fashion to work with a decentralized architecture. This federation creates opportunities in terms of data protection because data is held and managed more locally, close to the original owners and domain experts of the data. Data sharing between the components of such a decentralized architecture can be controlled in a fine-granular fashion, which allows for better guarantees in terms of data protection without sacrificing the data’s analytics value altogether. Learn how to design and assess decentralized data architecture and explore with us the requirements for technologies to support such architectures.
