Where Trusted Data Meets Responsible AI.
Artificial intelligence is changing the way companies use data, make decisions, and automate processes.
AI for Data Professionals is a hands-on, three-day training program that integrates AI and agentic AI with the disciplines critical to their successful implementation in the enterprise: data management, governance, and architecture.
Designed specifically for data professionals—not for AI engineers.
Trusted Data. Responsible AI. Practical Application.
You don't have to become an AI engineer to succeed in a company that is increasingly driven by AI.
But you should understand what AI is changing.
How does data quality affect AI outcomes? What role do metadata, lineage, and context play? How do data governance and AI governance interact? And what happens when AI systems no longer just generate content and recommendations, but increasingly carry out actions on their own?
These questions connect the worlds of Data Management and Artificial Intelligence more and more closely with one another.
It is precisely this connection that is the focus of this training program.
One program. Three days. A continuous learning journey.
The program covers everything from the essential fundamentals of AI and generative AI, through their connection to data management and governance, to the new world of agentic AI.
First, we'll lay the necessary groundwork. Then we'll examine what changes when AI begins to act independently.
DAYS 1–2
AI Fundamentals for Data Professionals
Laying the Foundation.
Understand the key principles behind artificial intelligence, machine learning, and generative AI—without needing a background in data science or software development.
You'll learn how AI relates to the data landscape you're already working in today, and why data quality, metadata, lineage, governance, and architecture are crucial for successful AI.
Key Topics
✓ Fundamentals of AI & Machine Learning
✓ Generative AI & Large Language Models
✓ Retrieval-Augmented Generation (RAG)
✓ Data Quality, Metadata, and Lineage for AI
✓ Data Governance & AI Governance
✓ AI Risks, Ethics, and Responsible Use
DAY 3
Agentic AI for Data Professionals
Understanding what changes when AI begins to act.
Agentic AI goes beyond systems that primarily generate content, perform analyses, or provide recommendations.
AI agents can interpret goals, plan steps, use tools, interact with other systems, and increasingly carry out actions on their own. This opens up new possibilities—but also creates new requirements for architecture, governance, and control.
Key Topics
✓ From Generative AI to Agentic AI
✓ Goals, Planning, Tools & Memory
✓ Agentic Autonomy
✓ Single-agent and multi-agent approaches
✓ Agents, Data, and Enterprise Systems
✓ Governance, Oversight, and Accountability
Individual AI tools will change. Models will continue to evolve. And prompts that are relevant today may already be outdated tomorrow.
That is why this training program takes a broader perspective.
It connects AI with the organizational environment in which it must operate:
DATA
Is the data understandable, reliable, and suitable for the intended purpose?
GOVERNANCE
Are responsibilities, controls, and decision-making authority clearly defined?
ARCHITECTURE
How does AI interact with data, applications, and business processes?
PEOPLE
Who evaluates and monitors the use of AI—and who is responsible?
The goal isn't simply to use AI. It's about understanding how data and AI need to work together.
This training program is specifically designed for:
Data Managers
Data Governance Professionals
Data Owners
Data Stewards
Data Architects
Data Quality Professionals
Metadata & Master Data Professionals
Data & Analytics Leads
Business Analysts
Data Consultants
CDMP Professionals
You don't have to be a data scientist, AI engineer, or software developer.
What matters most is your interest in understanding what AI means for the data and areas of responsibility you’re already working with today.
UNDERSTAND
Develop a clear understanding of AI, generative AI, and agentic AI.
CONNECT
Discover how data quality, metadata, lineage, governance, and architecture influence AI.
RATE
Assess the potential and limitations of AI beyond the current hype.
SHAPING GOVERNANCE
Understand the key issues surrounding risk, accountability, transparency, and oversight.
WORKING TOGETHER
Communicate and work more confidently with AI specialists, architects, other departments, and management.
APPLY
Apply what you've learned to specific issues and next steps within your own organization.
Erik Fransen
Director, Vista Veritas Data & AI Services
Ambassador & Guest Instructor – Connected Data Group & Connected Data Academy
Board Member – DAMA Netherlands
Editorial Board Member – The Trusted Data & AI Journal
Erik works at the intersection of data management, enterprise architecture, and artificial intelligence.
As an experienced trainer and consultant, he bridges the gap between technological developments and the requirements for data, governance, architecture, and organizational capabilities necessary for successful practical application.
Together with Dr. Michael Hahne, Erik is also one of the founders of *The Trusted Data & AI Journal*.
You don't have to become an AI engineer to succeed in a company that is increasingly driven by AI.
But you should understand what AI is changing.
How does data quality affect AI outcomes? What role do metadata, lineage, and context play? How do data governance and AI governance interact? And what happens when AI systems no longer just generate content and recommendations, but increasingly carry out actions on their own?
These questions connect the worlds of Data Management and Artificial Intelligence more and more closely with one another.
It is precisely this connection that is the focus of this training program.
One program. Three days. A continuous learning journey.
The program covers everything from the essential fundamentals of AI and generative AI, through their connection to data management and governance, to the new world of agentic AI.
First, we'll lay the necessary groundwork. Then we'll examine what changes when AI begins to act independently.
DAYS 1–2
AI Fundamentals for Data Professionals
Laying the Foundation.
Understand the key principles behind artificial intelligence, machine learning, and generative AI—without needing a background in data science or software development.
You'll learn how AI relates to the data landscape you're already working in today, and why data quality, metadata, lineage, governance, and architecture are crucial for successful AI.
Key Topics
✓ Fundamentals of AI & Machine Learning
✓ Generative AI & Large Language Models
✓ Retrieval-Augmented Generation (RAG)
✓ Data Quality, Metadata, and Lineage for AI
✓ Data Governance & AI Governance
✓ AI Risks, Ethics, and Responsible Use
DAY 3
Agentic AI for Data Professionals
Understanding what changes when AI begins to act.
Agentic AI goes beyond systems that primarily generate content, perform analyses, or provide recommendations.
AI agents can interpret goals, plan steps, use tools, interact with other systems, and increasingly carry out actions on their own. This opens up new possibilities—but also creates new requirements for architecture, governance, and control.
Key Topics
✓ From Generative AI to Agentic AI
✓ Goals, Planning, Tools & Memory
✓ Agentic Autonomy
✓ Single-agent and multi-agent approaches
✓ Agents, Data, and Enterprise Systems
✓ Governance, Oversight, and Accountability
Individual AI tools will change. Models will continue to evolve. And prompts that are relevant today may already be outdated tomorrow.
That is why this training program takes a broader perspective.
It connects AI with the organizational environment in which it must operate:
DATA
Is the data understandable, reliable, and suitable for the intended purpose?
GOVERNANCE
Are responsibilities, controls, and decision-making authority clearly defined?
ARCHITECTURE
How does AI interact with data, applications, and business processes?
PEOPLE
Who evaluates and monitors the use of AI—and who is responsible?
The goal isn't simply to use AI. It's about understanding how data and AI need to work together.
This training program is specifically designed for:
Data Managers
Data Governance Professionals
Data Owners
Data Stewards
Data Architects
Data Quality Professionals
Metadata & Master Data Professionals
Data & Analytics Leads
Business Analysts
Data Consultants
CDMP Professionals
You don't have to be a data scientist, AI engineer, or software developer.
What matters most is your interest in understanding what AI means for the data and areas of responsibility you’re already working with today.
UNDERSTAND
Develop a clear understanding of AI, generative AI, and agentic AI.
CONNECT
Discover how data quality, metadata, lineage, governance, and architecture influence AI.
RATE
Assess the potential and limitations of AI beyond the current hype.
SHAPING GOVERNANCE
Understand the key issues surrounding risk, accountability, transparency, and oversight.
WORKING TOGETHER
Communicate and work more confidently with AI specialists, architects, other departments, and management.
APPLY
Apply what you've learned to specific issues and next steps within your own organization.
Erik Fransen
Director, Vista Veritas Data & AI Services
Ambassador & Guest Instructor – Connected Data Group & Connected Data Academy
Board Member – DAMA Netherlands
Editorial Board Member – The Trusted Data & AI Journal
Erik works at the intersection of data management, enterprise architecture, and artificial intelligence.
As an experienced trainer and consultant, he bridges the gap between technological developments and the requirements for data, governance, architecture, and organizational capabilities necessary for successful practical application.
Together with Dr. Michael Hahne, Erik is also one of the founders of *The Trusted Data & AI Journal*.
The connection between data and AI extends beyond this training program.
Hahne Academy and The Trusted Data & AI Journal share a common perspective: The more AI is integrated into companies and their processes, the more important professional data management, responsible governance, and sound professional practice become.
The journal, launched by Dr. Michael Hahne and Erik Fransen, explores this intersection through independent perspectives from experts in data, AI, governance, and architecture.
"AI for Data Professionals" brings this perspective into the classroom.
AI for Data Professionals
December 7–9, 2026 | Hamburg
3-day in-person training · Training language: English
Registration fee: starting at €2,895 plus VAT.
For the entire 3-day training session
Days 1–2
AI Fundamentals for Data Professionals
Day 3
Agentic AI for Data Professionals
Coach: Erik Fransen
From the basics of AI to agentic AI—specifically for data professionals.
Additional dates for 2027 will be posted here shortly.
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