Data mesh is a sociotechnical approach to building a decentralized data architecture by leveraging a domain-oriented, self-serve design (in a software development perspective), and borrows Eric Evans’ theory of domain-driven design[1] and Manuel Pais’ and Matthew Skelton’s theory of team topologies.[2] Data mesh mainly concerns itself with the data itself, taking the data lake and the pipelines as a secondary concern. [3] The main proposition is scaling analytical data by domain-oriented decentralization.[4] With data mesh, the responsibility for analytical data is shifted from the central data team to the domain teams, supported by a data platform team that provides a domain-agnostic data platform.[5] This enables a decrease in data disorder or the existence of isolated data silos, due to the presence of a centralized system that ensures the consistent sharing of fundamental principles across various nodes within the data mesh and allows for the sharing of data across different areas.[6]