Data Mesh

From unstructured data lake to structured data mesh

From data lake to data mesh

How to get your data under control

Data Mesh enables your company to use data more efficiently and effectively. Established cloud architectures, enterprise architecture management and data governance are indispensable cornerstones.

We offer solutions

The data mesh structure contains many components. Together we find out whether and how this type of modelling fits your company and your challenges. We align our service with your current data maturity level and your existing or planned architecture.

How we reach our goal

From 4-hour workshops and data thinking in 2 days to 5-day pilot projects to finding and setting up a first data domain – we adapt to your needs.

Our key

We underpin data mesh with three disciplines: cloud architectures, enterprise architecture management and data governance, and also place your project in a suitable data maturity level.

The Maibornwolff Data Mesh Blueprint offers you these added values

Scalability and flexibility: Changes can be responded to iteratively and incrementally, through the standardisation of tools across divisions
Autonomy and domain-specific decentralisation: each team has control and responsibility over its own data

Higher data quality: Clear separation of tasks through decentralisation of data management and focus on data products
Better customer orientation through federal governance: target group-specific consideration of end-user needs

“Conducting an architecture assessment with MaibornWolff was crucial in identifying the necessary steps to establish effective data governance and evolve us into a data-driven company with a data mesh approach in the long term.”

Thorsten Mohr, Senior Data Analytics Specialist / Digital Transformation Unit, WEPA

Data Mesh comes to your company with Data Thinking

Our approach takes a holistic view of data mesh by considering technical, functional and organisational aspects. We combine data mesh with well thought-out data governance and digital data asset management. Our approach is divided into two phases:

1. Data Thinking

Stocktaking & detailed analysis – Only those who understand the business can make sound technical decisions. That’s why we first look at your business area and your data products. Based on this, we help you establish the appropriate data domains and make data products available to others.

2. Migration roadmap

Implementation plan & recommendations – As a result, you receive a sound catalogue of measures, with recommendations and concrete steps for all parties involved. We prioritise this migration roadmap together with you.
You can also benefit from our comprehensive, cross-sector expertise in the implementation of transformation and migration projects.

Data Thinking in action

Film off: Data Thinking Workshop with Bayernwerk

When transforming an unstructured data lake into a structured data mesh, the big picture must be taken into account right from the start. The video shows how this inventory analysis can be carried out with the help of the Data Thinking Workshop.