Data Mesh (Hamburg) - Dr. Simon Harrer & Jochen Christ - Deutsch
Description
In this training course, we will show you what the four principles of Data Mesh mean. You will learn about the challenges of introducing data mesh and receive recommendations for a step-by-step approach. Together we will design a data product, the central element in a data mesh, using our Data Product Canvas and show you the implementation alternatives. At the end of the workshop, you will be able to evaluate the socio-technical implications of Data Mesh and design data products.
The Data Mesh concept is based on domain-oriented, decentralized data architectures and enables development teams to perform data analysis autonomously. Data Mesh is a socio-technical data architecture and is presented in the form of the following four principles:
The “domain ownership” principle assumes that domain teams take responsibility for their data. According to this principle, analytical data should be structured in domains, similar to the team boundaries that correspond to the bounded contexts. Responsibility for analytical and operational data is transferred from the central data team to the domain teams.
The principle of “data as a product” applies the philosophy of product thinking to analytical data. This principle means that there are consumers for the data beyond the domain. The domain team is responsible for satisfying the needs of other domains by providing high-quality data as data products. Basically, the domain data should be treated like any other public API.
The third principle is to apply the “platform thinking” idea to the data infrastructure. A dedicated data platform team provides domain agnostic functions, tools and systems for the creation and consumption of interoperable data products for all domains.
The principle of “Federated Computational Governance” represents cross-organizational processes for data governance. This principle achieves the interoperability of all data products through standardization determined by the governance guild. The main objective is to comply with the organizational rules and regulations of the industry.
Agenda
The motivation behind Data Mesh. What are typical problems in data engineering that lead to the decentralization of data architectures?
When is data mesh the right approach?
The principle of “domain ownership”
The principle of “data as a product”
The “self-serve data platform” principle
The principle of federated computational governance
Design of a data product
Your Trainers
Dr. Simon Harrer
INNOQ
Passende Architektur, Clean Code, Remote Mob Programming
- Data Mesh for Managers
- Data Mesh: Introduction
- Online Team Event with Remote Mob Programming
Dr. Simon Harrer is a Senior Consultant at INNOQ. He is a software developer at heart who has now turned to the dark side, namely the world of data. He co-authored datamesh-architecture.com and translated the Data Mesh book by Zhamak Dehghani into German. He is currently developing the Data Mesh Manager, a SaaS product to fast-track any data mesh initiative.
Jochen Christ
INNOQ
Self-contained Systems, Autor von rest-feeds.org
- Data Mesh for Managers
- Data Mesh: Introduction
- Online Team Event with Remote Mob Programming
Jochen Christ is a Senior Consultant at INNOQ. He is an experienced software architect and Data Mesh specialist. He has supported over 10 companies in the introduction of Data Mesh. Jochen is co-author of datamesh-architecture.com, datamesh-governance, and datacontract.com.