INDUSTRY

Telecommunication

SIZE

9,000+ employees

DATA STACK

Kafka, Power BI, DataPen, Docker

SOLUTION

DataHub Core (OSS)

USE CASE

Discovery, Lineage, Governance

GOALS

  • Implement and scale data mesh for internal and external use cases
  • Make data products discoverable and addressable
  • Enable federated data governance across domains

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The Topline

Challenge
Needed to successfully implement and scale data mesh across their organization as the largest telco provider in the Netherlands

Solution
Implemented DataHub to organize domains, assign data products to owners, and track governance across their data mesh

Impact
Created discoverable, understandable, and addressable data products for both internal data mesh and public-facing Data Service Hub

Note: This story was originally published February 2024.

Challenge

As the largest telecommunications provider in the Netherlands, KPN faced the fundamental challenge of successfully implementing and scaling data mesh across their organization. The company needed to organize and manage their teams, groups, and functional areas while ensuring proper ownership, quality, and compliance of their data products.

The core challenge was creating a system that could make data products discoverable, understandable, and addressable while enabling federated data governance across all domains in the mesh. The organization needed a platform that could natively support their definition of a data product and facilitate metadata-driven workflows for compliance validation.

“If you consume data from multiple data products, then there must be some interoperability there.” 

 — Stefan Driessen, Data Scientist, KPN

Solution

KPN implemented DataHub as their foundational platform for a scalable data mesh. Specifically, they use DataHub to:

  • Organize and manage their teams, groups, or function areas as domains
  • Assign data products to specific owners and specific domains
  • Track and govern data products, ensuring ownership, quality, and compliance

KPN leverages DataHub’s rich, integrated support for data products to create metadata-driven workflows that can programmatically evaluate and validate compliance with policies and standards across all domains.

We track the lineage of the individual tables and the sets. And it’s great … DataHub is really good at that.

STEFAN DRIESSEN

Data Scientist, KPN

Impact

With DataHub, KPN successfully scaled its data mesh to support both its internal data program and public-facing Data Service Hub, one of the largest data spaces in healthcare and logistics within the EU. 

Key outcomes included:

  • Scaled data mesh across two strategic use cases, supporting both internal data program and external European data space partnership
  • User-friendly data discovery making data products discoverable, understandable, and addressable for consumers
  • Enabled federated data governance across all domains in the mesh
  • Simplified data access and sharing while maintaining consistently high data quality 
  • Streamlined security and compliance with integrated support for encryption, access controls, and auditing

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