The illustrations were created in cooperation between humans and artificial intelligence. They show a future in which technology is omnipresent, but people remain at the center.
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Digital Sovereignty in Corporate IT
Identify dependencies, assess risks, and develop effective IT strategies
This course is part of the certified Master Class "Machine Learning Engineer". If you book the entire Master Class, you save over 15 percent compared to booking this individual module.
Digital sovereignty is no longer merely a political buzzword, but a concrete technical and strategic issue for companies that use cloud services, AI systems, and modern platforms. In many IT environments, dependencies on vendors, proprietary technologies, or closed data formats are creeping in—often without a conscious decision and with direct implications for security, costs, innovation, and operational freedom.
In this practice-oriented training , you training how sovereignty in digital infrastructures can be assessed, technically classified, and operationally improved. With a focus on cloud, AI, and open-source architectures. The focus is on specific risks, architectural patterns, governance approaches, and technical measures that organizations can use to reduce their dependencies while simultaneously making productive use of modern platforms.
Contents
The Fundamentals of Digital Sovereignty
Concept, dimensions, and strategic significance.
Sovereignty vs. Self-Sufficiency.
Risks Associated with Modern Cloud and Platform Dependencies.
Practical examples and current developments.
Data sovereignty and regulatory requirements
Data residency, data portability, and open formats.
The Cloud Act, Schrems II, and the regulatory framework.
Encryption, key management, and privacy-enhancing technologies.
Gaia-X and European approaches.
Cloud Sovereignty and Architectural Patterns
Hyperscalers, EU tenders, and legal classification.
Lock-in risks and strategies for reducing dependencies.
Hybrid and multi-cloud approaches.
Kubernetes, open standards, and sovereign platform architectures.
AI Sovereignty and Open Source
Proprietary vs. open AI models.
Risks and Opportunities of Modern AI Stacks.
Open Source as a Factor in Sovereignty.
Community, licensing, and governance aspects.
Security, Governance, and Compliance
The relationship between security and digital sovereignty.
SBOMs, transparency, and auditability.
Governance models and organizational implementation.
Risk and Cost Assessment.
Effective solutions and practical implementation
Comprehensive solutions for key IT areas.
Architectural patterns for greater independence.
GitOps, IaC, and open APIs.
Roadmap for phased implementation within the company.
Your benefit
You understand the technical, organizational, and regulatory aspects of digital sovereignty.
You will learn to systematically assess risks and dependencies in cloud, AI, and platform architectures.
You can identify lock-in risks and mitigate them through appropriate architectural decisions.
You'll learn specific best practices for effective cloud, AI, and open-source strategies.
You will develop a realistic vision for increasing your company's digital capabilities.
trainer
Anastasia Vöhringer
Marcel Beyer
Methods
Professional insights and architectural analyses
Practical case studies and group work
Discussions and breakout sessions
Evaluation of real-world platform and cloud scenarios
The illustrations were created in cooperation between humans and artificial intelligence. They show a future in which technology is omnipresent, but people remain at the center.
AI-generated illustration
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AI-generated illustration
The illustrations were created in cooperation between humans and artificial intelligence. They show a future in which technology is omnipresent, but people remain at the center.