The data mesh: a distributed data architecture [Dutch spoken]

Initiatives such as digital transformation and becoming a data-driven organization are increasing the importance of data within organizations. Organizations want to do more with data. Their existing IT landscape is often inadequate, so something needs to change. Many are looking for solutions based on data lakes, data hubs and data factories, but a data architecture that is also well-worth considering is the data mesh. While data warehouses, data lakes and data hubs are primarily centralistic and monolithic solutions, the data mesh is a distributed solution. The data architecture is not broken down based on the nature of the application, but based on business domains. The division is no longer transactional systems versus analytic systems. As a result, traditional responsibilities within an IT organization will shift dramatically. For example, single-domain engineers responsible for transactional systems will also become responsible for the interfaces that provide analytical capabilities to the organization.

• The practical problems of centralistic and monolithic data architectures
• Differences between data mesh and data fabric
• From service interface to data product
• The importance of a foundation, or in other words ‘data infrastructure as a platform’
• The difference between a single-domain and hyper-domain data mesh
• The roles of data warehouses, data lakes and data hubs in a data mesh.