Data Mesh Architecture
Data Mesh Architecture
From the Engineering Perspective
About the Book
Data Mesh is a sociotechnical approach that enables development teams to autonomously carry out data analysis. Data Mesh leverages decentralization, a concept already familiar from modern software development with Domain-Driven Design, autonomous cross-functional DevOps teams, and microservices, and applies this consistently to the world of data and analytics. Data Mesh is based on four principles that are all interdependent: Domain Ownership, Data as a Product, Self-serve Data Platform, and Federated Computational Governance. In this primer, we explain Data Mesh from the engineering perspective.
About the Authors
About the Contributors
André Deuerling is IT-Consultant at INNOQ in Germany. He is a software engineer with expertise in C++, self-contained systems and a passion for building high-performance software systems. His interests include data mesh, domain-driven design and building right-sized applications.
Marco Steinke works as Consultant at INNOQ, where he specializes in software architecture. His professional interests also encompass artificial intelligence, with a particular emphasis on the design and incorporation of AI systems.
Table of Contents
- Intro
- Data Mesh at a glance
- What is Data Mesh?
- What is Data Mesh not?
- Why Data Mesh?
- Who will benefit from Data Mesh and who will likely not?
- Data analysis is becoming more natural
- Data Mesh by example
- Data Mesh Architecture
- Domain-oriented decentralization
- Data Products
- Data platform
- Governance
- Enabling
- Data Mesh in comparison
- Data warehouse
- Data lake
- Data virtualization
- Data fabric
- Conclusion
- Our services
- References
- About the authors
Other books by these authors
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