Dataspace Mesh
Glossary Page
A dataspace mesh (or mesh dataspaces) expands on the notion of a data mesh beyond an enterprise setting to include novel distributed, federated and decentralized data systems encompassing enterprise boundaries, like dataspaces. Merriam-Webster defines a mesh as “a web like pattern” or “an arrangement of interlocking links”, which corresponds particularly well with the intertwined dimensions of interoperability of systems including technical, semantic, organizational and legal.
https://cdn.dih.telekom.com/e930c2fe-b2ad-4183-86bb-27d0093f1a05
Latest Webinars
Latest Articles
TÜV Süd: Battery Pass verification via Catena-X
The demand for standardized, trustworthy battery passport data verification remains unmet. T-Systems and TÜV SÜD demonstrate an automated, transparent, and scalable verification solution, leveraging Catena-X integration, managed data rooms, and expert consulting to ensure regulatory compliance and trust.
Read more
Andrea Garcia
Mar 10, 2025
LEAP 2025: Innovation & data sovereignty in Saudi Arabia
At LEAP 2025, T-Systems and Detasad showcased cutting-edge dataspace solutions, driving secure data collaboration, AI innovation, and compliance in Saudi Arabia. Through strategic partnerships and cloud-agnostic platforms, we empower businesses to scale, optimize operations, and unlock new revenue opportunities in the region’s thriving digital economy.
Read more
Mohamed Radwan
Mar 03, 2025
Migrating Motion Data from On-Premises to AWS Cloud
This article outlines our experience migrating workloads from an on-premises data center to the AWS Cloud, culminating in the decommissioning of our last server in December 2024. The migration focused on our Motion Data product, which leverages geo-information analytics from Deutsche Telekom's mobile network to provide anonymized mass movement insights for industries such as retail, tourism, and public transport. Our transition to AWS was driven by rising colocation costs and the need to modernize our infrastructure, which faced limitations due to outdated technology constraints, high maintenance efforts, and inefficient storage and compute resource management. We selected AWS's Replatforming approach to harness managed services, improve scalability, and replace legacy Hadoop infrastructure with a more flexible Spark-on-Kubernetes and S3-based solution. The migration delivered key benefits, including 35% lower infrastructure costs, access to up-to-date technology stacks, and removal of resource constraints for compute workloads. By leveraging AWS-managed services such as Kubernetes (EKS), EMR, and RDS, we optimized performance, simplified operations, and positioned ourselves for future growth and innovation in cloud-native environments.
Read more
Dietrich Timm, Mohamed Radwan
Feb 26, 2025