Data mesh
Data Mesh is a architecture framework of an operating model for domain driven development of data products and applications that embraces the ubiquity of data in the enterprise by leveraging a domain-oriented, self-serve design (in a software development perspective), and borrows Eric Evans’ theory of domain-driven design. The main proposition is that instead of building large, centralized data platforms, enterprise data architects should create distributed datasets, or data meshes, that are managed by a particular group of human experts. These domain teams know how to design their data into data types and file formats that  will meet the needs of data consumers throughout an organization. History. The term "data mesh" was first defined by Zhamak Dehghani in 2019 while she was working as a principal consultant at the technology company ThoughtWorks. Dehghani introduced the term in 2019 and then provided greater detail on its principles and logical architecture throughout 2020. The process was predicted to be a “big contender” for companies in 2022. Data meshes have been implemented by companies such as Zalando., Netflix, Intuit, VistaPrint and others, thanks to software factories such as Agile Lab, "one of the very first [companies]in the world to  approach Data Mesh in a concrete way" Principles. Data mesh are now defined by 4 principles: In addition to these principles, Dehghani writes that the data products created by each domain team should be discoverable, addressable, trustworthy, possess self-describing semantics and syntax, be interoperable, secure, and governed by global standards and access controls. In other words, the data should be treated as a product that is ready to use and reliable.