Opleiding: Data Management for the AI Era (e-learning) (EN)
Do you want to work in a data-driven way or make use of AI? Then Data Management Foundation is essential for you!
Data Management Foundation helps you understand the key components of Data Management, develop a Data Strategy, and create an implementation plan for your organisation. This approach describes the Data Management components required to operate as an AI and Data-Driven Leader and achieve success in our data-driven world. The objective is to enhance your data management skills so that your organisation can manage data as a critical factor for business success.
This learning path is designed to provide a comprehensive framework for general data management while specifically enabling data management for Artificial Intelligence. Our approach to Data Management includes and goes beyond generic, process-based methods such as DAMA DMBOK2or FAIR by incorporating specific recommendations to manage data as a source of competitive advantage.
For anyone within an organization who bears responsibility for data or for the deployment of AI:
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CDOs / Heads of Data
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Members of the Data Governance Council:
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Data Governance Leads
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Data Owners
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Data Stewards
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Enterprise Architects
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CIOs
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Heads of AI & Analytics
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Compliance Officers, CISOs
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Internal audit / legal roles responsible for assessing data and AI risks
Our approach to Data Management incorporates and goes beyond generic, process-based methods such as DAMA DMBOK2 or FAIR by including specific recommendations to manage data as a source of competitive advantage:
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Recognizing Data Management as the infrastructure supporting every AI ambition, and identifying which Data Management disciplines strengthen or hinder your organization's AI capability.
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Working with a single, cohesive vocabulary that enables governance, architecture, business, and risk roles to collectively steer AI readiness.
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Assessing your organization's AI readiness based on concrete questions: where are the biggest gaps in governance, quality, architecture, security, and metadata?
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Understanding the architecture patterns recently introduced by the arrival of AI—such as RAG, vector databases, embeddings, and knowledge graphs—and understanding how these come together in a reference architecture for AI Data Management.
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Translating insights into the right next steps for your context: which disciplines require attention first, and what is the appropriate next step.
This learning path consists of:
- an eLearning consisting of a series of multi-media micro-learnings
- access to our AI playground in which you build your first AI models and can practice prompting
- quizzes to test your knowledge
- support via our AI 'learning buddy' to experience an Agent helping you
- examples of advanced agents including our EU AI Act Buddy
This e-learning provides a solid foundation for our Data-Driven Leadership programme. Furthermore, you can deepen your expertise in the world of AI by following programmes such as AI Ethics and the EU AI Act.
This training is an e-learning with the indicated study duration. It can also be followed as a blended programme, where you combine the e-learning with an additional one-day classroom session.
* Understand why data is vital today and why businesses struggle with it.
* Acquire foundational knowledge regarding the core concepts of ‘data’, ‘big data’, and ‘data management’.
* Learn how to manage data to create value from that data. * Discover the Data-Driven Leader’s approach to managing data.
* Develop your own data strategy (individually or as a team).
* Choose the infrastructure and vendors required to operate as a Data Leader.
* Implement data management in your organisation using our 5-step approach.
* Assess your data management maturity and continuously improve it.
The course references many external sources, including DAMA DMBOK2, FAIR, Linked Data, and all relevant ISO standards. See also: https://axveco.com/en/start-dmf-journey/
