The Data Product Marketplace: Enabling True Domain Ownership in Data Mesh
Data Mesh Live,DDD Europe - Sponsored Talk
- Speakers
Kris Peeters
- Description
The promise of data mesh lies in empowering domain teams to own and operate their data products. However, this fails when we expect business teams to work with the same complex toolchains that data engineers use. A collection of Airflow DAGs, Iceberg tables, and deployment scripts creates cognitive overload and becomes a barrier to adoption.
What domain teams need is a dedicated interface that bridges the gap between their business needs and the underlying data platform's capabilities. This is where a data product marketplace comes in - serving as a process-oriented single pane of glass for teams to discover, create, and consume data products.
Drawing from real-world examples, this talk will demonstrate how a data product marketplace can serve as this intuitive interface, offering standardized access to platform capabilities through business-friendly processes.
You will learn how this approach helps drive true domain ownership by helping teams:
- Discover and understand existing data products
- Create new data products following standardized processes
- Manage the entire lifecycle of their data products
- Collaborate across domains while maintaining clear ownership
- Ensure quality and governance
About Kris Peeters
Kris Peeters is the founder and CEO of Dataminded, a data engineering consultancy that helps organizations leverage data as a core asset in their digital transformation. With nearly two decades of experience in data and software engineering, he has led the implementation of data platforms and data mesh architectures for major enterprises across Belgium, including KBC, Telenet, and the Flemish Government.
He is also the driving force behind Conveyor Data, the product brand of Dataminded, helping organizations move from pipeline to product thinking and enabling data teams to build, govern, and scale their data products effectively.
Before founding Dataminded, Kris worked as a technology specialist at McKinsey & Company, where he drove numerous data initiatives and contributed to ETL tooling and designs for global clients. He brings deep expertise in cloud-native data architectures, production-grade data use cases, and practical implementation of data mesh principles.
A data engineer at heart and an active voice in the data community, Kris regularly shares insights about modern data platforms and data product thinking. He serves as a guest lecturer on big data at Solvay Business School's Executive Program in Business Analytics.