Is data mesh only for analytical data?

Is data mesh only for analytical data? This is a common question that arises when discussing data mesh with my customers. While data mesh is often associated with only analytical data, many of its principles can also be perfectly applied to operational data. In this blog post, we will explore how data mesh can be used for both analytical and operational use cases.

Operational data refers to the data that is used to run a business in real-time, such as transactional data and customer data. By applying data mesh principles to operational data, organizations can ensure that the data is of high quality, accessible, and can be used to drive (real-time) business decisions.

The operational data architecture contrasts with the analytical data architecture because the operational plane processes commands and requires predictability and real-time processing of small datasets, while the analytical plane focuses on data reads and requires complex data analysis, which uses large datasets and isn’t that time-critical. However, there’s a large amount of overlap in the domain model, how events and APIs (like data) should be treated as products, and how the boundaries between applications and domains should be set. Your business capabilities are the same when looking at your architecture through an operational or analytical lens. The applications that provide these capabilities have teams behind them that manage them and ensure they stay up and running. The language that the team uses for development is the same. Ultimately, the unique…