Data Strategy That Leads To Better Decisions
Modern data platforms are rarely limited by the tools alone. The harder question is whether the organization can trust the data, understand the trade-offs, and turn analytics into decisions that move the business forward.
My advisory work is for teams that need a clearer path: what to improve first, which platform choices are worth making, where quality issues are created, and how to make data useful evidence for both people and AI.
Where I Can Help
I work with organizations that want to make their data platforms more reliable, more understandable, and more useful for decision-making.
- Data strategy and roadmap reviews
- Data quality and trust assessments
- Microsoft Fabric, SQL Server, Azure SQL, Azure SQL Managed Instance, and PostgreSQL advisory
- Analytics architecture and platform modernization
- Automation opportunities for data engineering and operations
- Practical governance that supports delivery instead of slowing it down
- Readiness for AI-supported analytics and decision processes
My Perspective
I have worked with data since 2008, across database administration, business intelligence, data engineering, automation, and applied data science. My background is hands-on and technical, but the advisory focus is strategic: how data platforms become useful evidence for the business.
Good data strategy is not only about choosing technology. It is about making clear decisions on ownership, quality, reliability, automation, documentation, and how people actually use data in their daily work. For the personal background behind this perspective, see About me.
I bring a pragmatic view from hands-on implementation and community work. I care about solutions that can be operated, explained, improved, and trusted.
Education note: Master of Advanced Studies (MAS) in Business Intelligence, HWZ Zurich. My 2024 diploma thesis examined financial reports with generative AI on Microsoft Fabric, using a RAG model and GPT-3.5.
Typical Questions
- Can we trust the data behind our reporting and AI initiatives?
- Where are quality problems created, and how can we prevent them earlier?
- Is our data platform helping business teams make decisions, or mainly producing more dashboards?
- What data architecture do we need?
- What should move to Microsoft Fabric, Azure SQL, or another platform, and what should stay where it is?
- Where would automation reduce risk, manual work, or recurring incidents?
- Are we doing enough to protect sensitive data?
- How do we design governance that people will actually follow?
- What does a realistic data roadmap look like for the next 6 to 18 months?
How An Advisory Engagement Can Look
Advisory work can be small and focused, or broader depending on what you need. A useful starting point is often a structured review of your current data landscape, pain points, decision processes, and platform direction.
From there, I can help you identify priorities, risks, quick wins, and longer-term architectural choices. The outcome should be understandable for both technical teams and decision-makers.
Possible formats include:
- A focused strategy call
- A platform or data quality review
- A workshop with technical and business stakeholders
- A roadmap review
- A second opinion on a planned architecture or migration
- Support for internal presentations about data strategy, quality, or accessibility
Let’s Talk
If you want to discuss data strategy, data quality, Microsoft data platforms, or how to make analytics more useful for real decisions, use the contact form.