Modern Data Architectures for Scalable Data Strategies
With Data Mesh, you make your data architecture scalable, eliminate central bottlenecks, and establish clear accountability for data — directly within your business domains. The result: faster decisions, more efficient processes, and sustainable competitiveness.
How to Successfully Implement Data Mesh in Your Organization
We support you throughout your Data Mesh journey — from the initial assessment to full operational implementation.
Where does your organization currently stand — and where do you want to go? We analyze your starting point and develop a target vision aligned with your strategic goals, including an evaluation of whether Data Mesh or a more centralized model is the better fit.
How much effort is required, and where is the best place to start? We identify initial pilot areas (“incubators”) and clarify which prerequisites must be met to ensure the new data operating model is well integrated into your organization.
Who owns which data products? We help you establish a clear assignment of data responsibilities to teams and domains — creating the foundation for decentralized ownership and scalability.
Which technical components do you need for self-service, governance, and orchestration? We support you in selecting and designing a platform that optimally enables your Data Mesh strategy.
How do processes interact, and who takes on which role? Together, we define an operating model that combines standardized workflows with the flexibility required for domain-specific needs.
Knowledge, tools, and feedback — exactly where you need them. We provide targeted enablement and act as a sparring partner to guide and strengthen your organization throughout the implementation process.
Data Mesh: More Than Just Technology – A New Organizational Model for Data
A Data Mesh is not a software solution — it’s an organizational model with technical prerequisites. These include:
- A platform that enables easy creation and consumption of data products.
- Unified standards for data governance, lineage, and access control.
- Tools for automation, monitoring, and quality assurance.
- And most importantly: clear roles, processes, and responsibilities.
Data Mesh Is Not an End in Itself
It’s not about following the latest hype — it’s about making data truly effective: flexible, decentralized, scalable, and closely aligned with the business — wherever it makes sense. You don’t need new software. You need impact.
Let’s find out together whether Data Mesh is the right approach for your organization.
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FAQs Data Mesh
A Data Mesh is a decentralized organizational model for analytical data. It shifts responsibility for data from central teams to individual business domains, which create, manage, and provide their own data products.
Viele Unternehmen stoßen mit zentralisierten Datenplattformen an ihre Grenzen: Daten-Teams werden zum Engpass, wenn sie alle Anforderungen bedienen müssen. Data Mesh löst dieses Problem durch domänenorientierte Verantwortung und fördert schnellere, skalierbare Datenanalysen.
- Domain Ownership: Business domains are responsible for their own data.
- Data as a Product: Data is treated like a product — with clear quality and usability standards.
- Self-Service Data Platform: A central platform enables all teams to easily create and consume data products.
- Federated Governance: Unified standards and policies ensure interoperability and compliance.
No. Data Mesh is not a tool — it’s an organizational approach. While platforms, tools, and technical standards are essential, they’re not sufficient on their own. The real success depends on cultural and process transformation.
A data product is a logically defined unit that processes, stores, and exposes data through defined interfaces (output ports). It is managed by a domain team and follows a clear lifecycle management process.
Governance is federated: a governance committee composed of multiple teams defines global standards for interoperability, security, documentation, and compliance. These standards are then enforced automatically through the platform.
Implementation typically begins with pilot domains, supported by an “enabling team” that provides expertise and guidance. A clear change management approach is essential — redefining roles, processes, and responsibilities to ensure sustainable adoption.