Data Mesh Consulting for Scalable Data OrganisationsDomain ownership, data products and federated governance – introduced pragmatically, not dogmatically
With our Data Mesh consulting, you move responsibility for data to where the expertise lies: in the business domains. We assess with you whether and to what extent Data Mesh fits your organisation, start with a first data product and build the platform and governance step by step.
Qlik Talend, Databricks, Snowflake
partner for data integration
certified information security
of experience in data projects
The four principles of Data Mesh
Data Mesh is not a product but an organisational and architectural approach. Instead of concentrating all data in one central team, business domains take responsibility for their data – on a shared platform and according to shared rules.
Domain ownership
The business units that create and best understand data are also responsible for its quality and provision.
Data as a product
Data is treated like a product: discoverable, documented, reliable and with clear owners.
Self-service platform
A shared data platform takes technical work off the domains so they can focus on content.
Federated governance
Common standards for security, quality and interoperability – agreed centrally, implemented locally.
When Data Mesh fits – and when it does not
Data Mesh solves scaling problems but also creates coordination effort. That is why we assess honestly whether the approach suits your situation – or whether a well-organised central data warehouse or lakehouse is the better choice.
Data Mesh fits if …
- the central data team has become a bottleneck
- many business units have their own data requirements
- domains can be clearly separated in business and organisational terms
- the organisation is ready to distribute responsibility
Rather not if …
- there are only a few data sources and use cases
- there is no budget for a shared platform
- business units have no capacity for data ownership
- basic data quality and governance are still missing
Four steps to Data Mesh
We do not introduce Data Mesh as a big bang. We prove its value with a first data product and then scale.
Maturity and target picture
We analyse organisation, data landscape and governance maturity and clarify whether and how far Data Mesh makes sense.
Pilot domain and first data product
Together with a suitable domain, we develop a first data product including ownership and quality rules.
Platform and governance
We build the self-service platform and the federated standards for security, metadata and interoperability.
Scaling
Further domains follow a proven pattern – supported by training and clear roles.
Implemented vendor-neutrally
Data integration
Clean data flows into and between domains with Qlik Talend, streaming and API integration.
Lakehouse and cloud DWH
Databricks or Snowflake as a shared platform for storage, processing and analytics.
Data catalog
Make data products discoverable with Collibra, Alation or DataHub.
Data contracts and quality
Define interfaces, quality rules and ownership for each data product in a binding way.
Access and security
Role-based permissions and data protection defined centrally, implemented in the domains.
AI on data products
Well-described data products are the best foundation for AI applications and agents.
Frequently asked questions about Data Mesh consulting
What is Data Mesh?
Data Mesh is an organisational and architectural approach in which business domains take responsibility for their data and provide it as products. A shared platform and federated governance ensure that the data products fit together.
Is Data Mesh a piece of software you can buy?
No. Data Mesh describes how responsibility, processes and architecture are organised. It is implemented with existing technologies such as lakehouse platforms, data integration tools and data catalogs.
Does Data Mesh replace our data warehouse?
Not necessarily. A data warehouse or lakehouse can be part of the self-service platform. Data Mesh mainly changes who is responsible for which data and how it is provided.
Which companies benefit from Data Mesh?
Above all organisations with many business units, numerous data sources and a central data team that has become a bottleneck. For smaller data landscapes, a central approach is often simpler.
How long does the introduction take?
A first data product can usually be delivered within a few months. Rolling out to further domains is a gradual process whose pace depends on the organisation and its maturity.
What role does data governance play?
A central one: without common standards for quality, security and metadata, new data silos emerge. Learn more about our data governance consulting.
Does Data Mesh fit your organisation?
Let us assess together whether Data Mesh is the right path for you and where a first data product will deliver the greatest value. We will get back to you promptly for a free initial consultation.
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Note: This text was created or revised with the support of AI.