Data Mesh: Discover corporate data faster and use it more efficiently

The starting point: heterogeneous data landscape and responsibilities, diverse data quality and usability

The REWE Group faced the challenge of making corporate data usable faster and more effectively for both operational and analytical processes. The historically grown data landscape made it difficult to deliver tailored data directly for operational and analytical use.

The Vision: Data consumers should be able to "shop" curated data independently and easily — just like products in a supermarket. The Data Mesh concept, as a modern data management paradigm, promised the right solution. Instead of one large central data model, many small, curated data products should take its place — equipped with clear responsibilities and implemented on a self-service data platform.

In addition to self-service data usage, manual and labor-intensive processes around data preparation and provisioning were to be automated. The goal was to pilot this new concept at REWE Group and prepare for its subsequent scaling.

Our Approach: anchoring data mesh principles in the data platform and evaluating them through initial data products

The project centered on a Data Mesh approach aligned with business value from the very beginning. The aim was to establish data as products within the company, anchor data responsibility within business data domains, enable self-service data usage, and ensure fundamental data governance is automated within the data platform.

The piloting of the Data Mesh concept tailored to REWE Group was carried out using selected data products, prioritized by value with the help of data landscapes for each data domain. Some data products were technically re-implemented in the data platform based on business requirements, while others already existed and could be published directly in the data catalog.

To make the data products easy to use, new Data Shopping processes were defined and implemented in the Collibra governance and data catalog as well as in the Snowflake data platform. These included, for example, automated access permissions and data quality certifications. To prepare Data Mesh at REWE Group for scaling, a comprehensive change and enablement plan was also designed, and a Data Board was established as a steering committee. In doing so, the project team not only gained the full support of management but also ensured active involvement from the business units.

Why PwC?

Implementing a Data Mesh is not purely a technology question, it is, above all, an organizational transformation. PwC combines deep industry expertise with technical excellence in the design and implementation of modern data platforms, along with effective change management methods. Our experts are well-versed in Data Mesh approaches and have been applying them in various projects for several years. With PwC, you benefit from an interdisciplinary team that not only rolls up its sleeves technically and builds a working platform with you, but also creates the right organizational framework and empowers your employees so that you are successful in the long term.

The Added Value

Through the piloting of Data Mesh at REWE Group, the value of the concept was proven in practice — laying and confirming the foundation for company-wide scaling. The data catalog enables faster discovery of relevant data products. Through Data Shopping, data products are made available quickly and efficiently. Data quality checks continuously increase the reliability of the data, ensuring dependable management of business processes and enabling new analyses and AI use cases.