- Vorwort
- Data Mesh im Überblick
- Was ist Data Mesh?
- Was ist Data Mesh nicht?
- Warum Data Mesh?
- Für wen ist Data Mesh sinnvoll und für wen eher nicht?
- Datenanalysen werden selbstverständlicher
- Data Mesh am Beispiel
- Data-Mesh-Architektur
- Domänenorientierte Dezentralisierung
- Datenprodukte
- Datenplattform
- Governance
- Enabling
- Data Mesh im Vergleich
- Data Warehouse
- Data Lake
- Data Virtualization
- Data Fabric
- Fazit
- Unser Angebot
- Literaturhinweise
- Über die Autor:innen
Data Mesh Architektur
Aus der Engineering-Perspektive
In diesem Primer erklären wir Data Mesh aus der Engineering-Perspektive.
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Data Mesh ist ein sozio-technischer Ansatz, der es Entwicklungsteams ermöglicht, Datenanalysen autonom durchzuführen. Data Mesh setzt auf Dezentralisierung, die wir bereits aus der modernen Softwareentwicklung mit Domain Driven Design, autonomen, funktionsübergreifenden DevOps-Teams und Microservices kennen, und wendet diese konsequent auf die Welt der Daten und der Analyse an. Data Mesh basiert auf vier Prinzipien, die alle voneinander abhängen: Domain Ownership, Data as a Product, Self-serve Data Platform und Federated Computational Governance. In diesem Primer erklären wir Data Mesh aus der Engineering-Perspektive.
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About the Authors
Dr. Simon Harrer
Dr. Simon Harrer is a senior consultant at INNOQ. In his daily business, he fights for simple solutions with domain-driven design, fitting architectures such as microservices or monoliths, and clean code in Java, Ruby or even JavaScript. Most recently, he wrote the book Java by Comparison that helps Java beginners to write cleaner code through before/after comparisons.
Jochen Christ
Jochen is a senior consultant at INNOQ. As a specialist for modern Java technologies, he creates elegant solutions with innovative architecture concepts, such as Microservices, Serverless and cloud computing. Jochen is interested in agile methods, clean code and usable security. He is a speaker at international conferences and enjoys participating in local meetups.
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