Parallax Background. Click to change options.This block is visible only in page builder. You can place this block in any position of section. Add only one custom background (parallax, zoom, video) for one section.
MicrosoftTeams-image (1)

Data Mesh

Download the free white paper now and learn how leading companies like HelloFresh and Zalando benefit from this innovative approach to data management.

Data Mesh in Practice:
Data to the People

In the data scene there was no way around this topic in the past years:
Data Mesh. At its core Data Mesh gives the data back to the people who created the data. Companies such as HelloFresh, Zalando, adidas and Delivery Hero successfully use the concept as the foundation for their data management. For companies for which data and its use represent a strategic advantage, Data Mesh is the solution to leverage data potential on a large scale. The focus is on scaling the use of data.


What is Data Mesh?

Data Mesh is a new approach or strategy for data management. Important building blocks of this approach are the decentralisation of data and the understanding that data are strategic assets. Data Mesh is an answer to central data teams that reach their limits at a certain point: decreasing innovation rates, increasing time-to-market, general frustration regarding data quality and availability. Data Mesh builds on the concept of Domain Driven Design by Eric Evans and extends it to include the aspect of data. 

Founder Zhamak Dhegani aptly summarises Data Mesh: "Data Mesh is not just an architecture, it is not just a technology, it is not just an organisational change, it is all of the above. It's a paradigm shift in the way we manage Big Data at different levels."


Does data mesh make sense for my business?

Delve deeper with our compact white paper that provides a comprehensive and organized overview of Data Mesh.
Discover what lies behind the 4 principles and gain insight into how Data Mesh operates in real-world scenarios.

The four main principles of Data Mesh

Domain ownership

Decentralization and distribution of data responsibility to people who are closest to the data

Data as a product

This comes down to two main interpretations: Data is treated as a product. Therefore, consumers of data should be treated as customers.

Self-serve data infrastructure

Reduces the effort needed to build data products and therefore speeds up the process and increases quality through standardization


In a mesh of independent data products a federated governance ensures trust and security