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Data architecture, the decisions it is for, and the AI that sits on top. Plain words, real cases, and something to try in every one.
When each department works with its own data, the numbers don't add up and meetings get spent debating figures instead of making decisions. Here I explain why it happens and how to fix it.
AI & data · 4 min readInteractiveWhy your AI gives bad answers (rarely the model)When an AI project fails, the model is rarely the reason. Why it happens, and how to check your data before you invest more in AI.
Metrics & KPIs · 3 min readInteractiveUseless KPIs: how to define the ones that help you decideMost companies have too many KPIs and none that are useful. Learn to tell operational metrics from strategic ones and to define indicators that truly support decision-making.
Startups & investment · 4 min readInteractivePreparing Your Data Before Talking to an InvestorBefore a funding round or due diligence, you need coherent, traceable and verifiable data. Here are the metrics you cannot skip and how to avoid the most common mistake.
Data governance · 6 min readInteractiveData ownership: put a name on every numberData governance in a mid-sized company is not fixed with a committee or a policy document. It is fixed by putting one name next to every number that matters.
AI & automation · 3 min readInteractiveAI in your company: where to start without wasting timeAI automation creates a lot of noise and few concrete answers for SMEs. Here I explain what makes sense to implement, in what order, and what isn't worth it yet.
Data team · 5 min readInteractiveWhy hiring a data analyst won't fix your dataBefore you hire an in-house data analyst for your company, there is one question almost no one asks. Why the problem is rarely solved by hiring.
Business Intelligence · 4 min readInteractiveDashboard vs. a Real View of Your BusinessHaving a dashboard does not mean you have real visibility into your business. Here is what sits behind good data-driven decisions and why the difference matters.
Decision Intelligence · 4 min readInteractiveQuerying your data in natural language: real vs. hypeCopilot, Power BI Q&A, text-to-SQL: the promise of talking to your data like a person is here. When it truly works, when it breaks, and what you need in place first for it to help a small business.
Data infrastructure · 3 min readInteractiveWhen does a growing company need a data warehouse? (and when not)A practical guide to knowing if your company needs a Data Warehouse. Three concrete signals that it's time, and situations where it's not worth it yet.
Data strategy · 3 min readInteractiveWhat data maturity level is your company at?Find out what data maturity level your company is at with 3 concrete questions. No technical jargon, with real examples from small and mid-sized companies.
Business Intelligence · 4 min readInteractiveThe 5 most common Power BI mistakes (and how to avoid them)Power BI is easy to use but hard to use well. These are the 5 mistakes I see most in real Power BI projects at small and mid-sized companies, and how to avoid them.
AI & regulation · 7 min readInteractiveWhat the EU AI Act asks of a growing company in 2026Updated October 2026. After the Digital Omnibus, transparency has applied since August 2026 and high-risk rules move to December 2027 and August 2028. What affects you if you use AI, and where to start.
You know your data is a mess. That's the best place to start.
I design how data reaches the people who decide, fast and correct, in a way your team can use, grow and keep running long after I've gone. Tell me what you need to decide, and where the data gets in the way.
Rather ask your own AI? It opens with the question already written: who I am, how I work, what it costs and whether I fit your company. It reads this site and answers in its own words.