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Concepts
16 articles in the Concepts topic.
AI literacy: what the AI Act asks of employees, management and supervisors
AI literacy is knowing what AI can do, what it can't and where the risks are. What the AI Act still requires after the Digital Omnibus, and how to approach it by role.
NIS2 and the Dutch Cybersecurity Act: what your data and AI layer must be able to prove
The Dutch Cybersecurity Act (NIS2) has applied since 15 August 2026. What it requires, who is in scope and what your data platform and AI must be able to demonstrate.
The AI Act in the Netherlands: which law applies and who supervises
The AI Act applies directly. The Dutch implementation act sets who supervises: ten authorities, with the AP and RDI coordinating.
What is the EU AI Act? What applies now and what applies from December 2027
The AI Act regulates AI by risk. Which obligations already apply, what the Digital Omnibus postponed, and what your organisation needs to arrange now.
RAG or fine-tuning? Choosing for your own company data
Retrieve at question time or train the model further: the choice depends on how often your knowledge changes and whether you must be able to point at the source.
Implementing AI: why it almost always stalls on your data
The model is rarely the problem. Pilots stall because nobody can retell where an answer came from, or who owns the terms inside it.
What is data governance? Roles, agreements and evidence
Data governance is not a policy document. It is the agreement about who owns which term, what it means, and how you can still retell that six months later.
What is master data, and why does your reporting depend on it?
Customer, item, location and supplier: the data that shows up everywhere. When it is wrong, no report above it is right.
Effective data lifecycle management
Data has a life: created, used, retained, removed. Skip a phase and you pay twice - in storage, and in wrong answers.
What is a data platform? The layers, the choices, the pitfalls
A data platform is not a tool you switch on. It is the layer where your data comes together, gains meaning and becomes reusable. Here is what that layer looks like.
What is a company brain?
A company brain is the layer where your organization''s knowledge is captured, so people and AI can build on the same understanding. Not a dashboard, not a chatbot: a foundation.
What does AI Native mean?
AI Native does not mean you bought AI. It means your organization is set up so intelligence can do real work in it: definitions captured, data reliable, decisions owned.
What is a data contract?
A data contract is an agreement about what data means, who supplies it and what happens when it changes. It is how a definition gets an owner instead of an opinion.
What is a data mesh?
A data mesh puts ownership of data with the domains doing the work instead of one central team. What that buys you, and what to settle first.
What is data architecture?
Data architecture is the layout that decides where data arrives, where meaning is recorded and where answers come from. Four layers, and the choices that recur.
What is Databricks?
Databricks is a lakehouse platform: storage, processing, catalogue and models in one place. What it does, what it does not do, and when it is the right call.
Start with one decision that has to get better
Pick a recurring question where teams lose time or contradict each other. Make the meaning behind it explicit and bring it straight into daily operations.