Data Mesh
The Future of Data Management and Sharing
The cradle of Data Mesh
Building a data-oriented business remains one of the top strategic goals of organizations and executives. And while it may seem logical for companies to embrace the idea of being data-driven, it’s far more difficult to execute on that idea.
Changing landscape of data expectations
Data expectations used to be limited to Business Intelligence (BI) with reporting and dashboards. Today’s data however demand:
- the integration of machine learning and real-time
- data-driven optimizations
- streamlining operations (e.g. real-time logistics)
- democratization of data
- continuous, frictionless access to the latest data
Traditional data architectures and data lakes become overwhelmed and are unable to scale and evolve with those demands. This is where the principles of data meshes come into play. They provide answers by enabling greater autonomy and flexibility for data owners, facilitating data innovation, while lessening the burden on data teams with a decentralized approach.
Revolutionize Your Data Strategy
Data meshes answer the challenge of managing data by focusing on building a decentralized, self-serve data ecosystem. By allowing greater flexibility for data stakeholders and lessening the burden on data teams, it addresses many common challenges and problems associated with traditional data management and data sharing practices:
![]()
Unleash siloed dataIn many organizations, data is stored and managed in isolated silos, making it difficult to access and share data across teams and departments. A data mesh aims to break down these silos and enable data to flow freely and easily across the organization.
![]()
Stop playing catch-upTired of playing catch-up with your data in a complex and volatile business environment? Data meshes allow you to manage changes to data gracefully. They align business, tech and data, while reducing the accidental complexity of pipelines and copying of data.
![]()
Reduce extensive coordinationReduce heavy coordination by delegate responsibilities to autonomous domains and their data product owners. Automate governance policies as embedded code and introduce explicit data contracts between data products to ease coordination.
Get started with Data Mesh
Identify Data Mesh Possibilities
We will work together in mapping out the relevant source systems of data and associated data products and thus make the possibilities of a data mesh visible.
Is Data Mesh the right solution for you?
Use our interactive decision tree to determine if Data Mesh is the right solution for you.
Join the Data Mesh Meetup
This community is open to all people who are passionate about Data Mesh in Belgium. We want to stimulate sharing data mesh experiences, organizing events and come-togethers for everyone whose interested.
How does Data Mesh work?
Data mesh is an approach towards data management within organizations. The idea is to increase the accessibility and availability of data to business users and reduce the interdependency between data teams. It is based on the principles of modularity and governance, where data is treated as a first-class citizen with its own independent lifecycle and management structures. Let’s have a look at the key advantages for your organization when implementing a data mesh.
- Team autonomy with minimal dependencies to drive decision making
- Transparency for cross-functional use between teams
- Improved agility and flexibility in data management
- Enhanced data governance
- Breaking up data silos by sharing and making data reusable
- Seamless integration with emerging technologies
Traditional data approach vs data mesh
Decentralized approach
Imagine that a company has a large amount of data spread across multiple departments and systems. In a traditional data management approach, each department might have its own siloed systems (a data silo is a collection of data held by one group that is not easily or fully accessible by other groups in the same organization) for storing and managing data, making it difficult for teams to access and share data with each other. With a data mesh, the company could adopt a more decentralized approach to data management.
Each department would still have its own systems for managing data, but these systems would be connected and interoperable, allowing for easy sharing and access to data across the organization. Additionally, the company could establish clear governance protocols and standards for managing data, ensuring that it is used consistently and in accordance with company policies.
Data Mesh News
- Applying Data Mesh principles to an IoT data architecture
This blog post shows how a data mesh approach avoids an unmaintainable monolithic data platform by explaining what data mesh is, its principles and applying it to an IoT data case as an example.
- ACA Group launches first Data Mesh Meetup
This community is open to all people who are passionate about Data Mesh in Belgium. We want to stimulate sharing data mesh experiences, organizing events and come-togethers for everyone whose interested.
- The impact of a changing application landscape on your data architecture
Cloud solutions, self-service applications and other innovations are complicating data architecture. Discover their impact in this new blog post!
Want to know more about Data Mesh?
Want to identify your Data Mesh opportunities? Intersted in finding out more about Data Mesh? Contact our Data Mesh expert Tom De Wolf for more information or send us a message via our website chat.
