Architectural Design Decisions for Self-Serve Data Platforms in Data Meshes
Tom van Eijk, Indika Kumara, Dario Di Nucci, Damian Andrew Tamburri, Willem-Jan van den Heuvel
TL;DR
The paper addresses the challenge of designing self-serve data platforms within data meshes. It constructs a catalog of architectural design decisions (ADDs) and options by systematically reviewing 43 industrial gray-literature sources and validating them through six semi-structured interviews with data-mesh practitioners. The ADDs are organized across three planes of the self-serve platform—Data Infrastructure Utility Plane, Data Product Experience Plane, and Data Mesh Experience Plane—covering governance, deployment, product APIs, discovery, and mesh governance. The work provides a practical baseline to guide platform teams, accelerates data-mesh adoption, and lays groundwork for an interactive decision-support tool.
Abstract
Data mesh is an emerging decentralized approach to managing and generating value from analytical enterprise data at scale. It shifts the ownership of the data to the business domains closest to the data, promotes sharing and managing data as autonomous products, and uses a federated and automated data governance model. The data mesh relies on a managed data platform that offers services to domain and governance teams to build, share, and manage data products efficiently. However, designing and implementing a self-serve data platform is challenging, and the platform engineers and architects must understand and choose the appropriate design options to ensure the platform will enhance the experience of domain and governance teams. For these reasons, this paper proposes a catalog of architectural design decisions and their corresponding decision options by systematically reviewing 43 industrial gray literature articles on self-serve data platforms in data mesh. Moreover, we used semi-structured interviews with six data engineering experts with data mesh experience to validate, refine, and extend the findings from the literature. Such a catalog of design decisions and options drawn from the state of practice shall aid practitioners in building data meshes while providing a baseline for further research on data mesh architectures.