DatazinnıgRuud van Cruchten

Ruud van Cruchten

Data scientist and independent advisor

Ruud van Cruchten

Profile

Questions about data and AI always touch several disciplines, from strategy and operations to architecture, data quality, technology and societal impact. I bring those perspectives together. As an advisor, I hold the conversation with the board and management. As a data scientist and architect, I design and deliver the solution myself. That makes my advice strategically grounded and feasible.

I built that combination over more than ten years of practice. In that time the field evolved from static reports via dynamic dashboards to machine learning and AI agents. At the consultancy firm Ponthus I grew to senior consultant and worked for organisations across a wide range of sectors. Within PWCo, Ponthus's joint venture for housing associations, I led the content of data and BI programmes and developed a data platform for the sector. At grid operator Enexis I worked as data architect and data scientist on asset management, in the middle of a profound transformation.

What drives me is curiosity. During my PhD research on process mining and data quality I learned to bring complex matters back to their core, quickly and systematically. I deliberately keep my knowledge of AI current, among other things through the data scientist programme at EAISI Academy of Eindhoven University of Technology. As an independent advisor I choose independence, without commercial interests and with integrity as a given. I am glad to work for organisations with a social purpose.

Collaboration

Clients and colleagues know me as a good listener. I am empathetic, helpful and genuinely interested in the people behind a question. At the same time I think quickly and sharply. I keep asking until the core is clear and look beyond today's question. I am honest and constructively critical, even when that is the harder message, and I bring everyone along in the choices that follow.

Career

2026 – present
Owner, data scientist and advisor Datazinnig

Independent advice and delivery in data strategy, data architecture and AI.

2024 – 2026
Analyst and data architect Enexis

Data architecture, solution management and data science for the Asset Information Management department.

2015 – 2023
Senior Consultant Data Science & Product Manager Ponthus

Advice and delivery in data strategy, data architecture, BI and data science. Within PWCo responsible for housing sector programmes and a data platform for the sector. Coach of junior consultants and graduate students every year.

2019 – 2023
PhD research, part-time Tilburg University

Process mining as the basis for data-driven enterprise architecture, with a focus on data quality.

Education

2025 – 2026
Data Scientist (Mastering Data & AI) EAISI Academy, Eindhoven University of Technology
2016 – 2017
MSc Information Management, cum laude Tilburg University
2016 – 2017
MSc Global IT Management, magna cum laude University of Turku, Finland
2012 – 2015
BSc Business Economics and Informatics Tilburg University

Expertise

Data and AI strategy

Determining where data and AI demonstrably add value, and setting a feasible course in line with the existing architecture and strategic ambitions.

Data and information architecture

Design of data platforms, data warehouses and information models, and the translation of reference architectures to the organisation.

Data governance and data quality

Making data quality measurable and structurally assured following DAMA-DMBOK, with clear responsibilities.

Data science and analytics

Machine learning in Python across the full analytical cycle, from problem definition to a model in production.

Generative AI and agents

Language models, AI agents and computer vision, with the preconditions for successful use, such as reliable data, unambiguous definitions and ontologies.

Business intelligence and process mining

Management information and process insight that match the real question, with indicators that genuinely support decisions.

Technologies

Programming and engineering
Python, SQL, ETL, datawarehouse-ontwerp
Analysis and AI
Machine learning, process mining, Power BI, Qlik
Platforms
Microsoft Fabric, OneLake, Azure, Power Platform
Modelling
ArchiMate, UML, ERD
Open-source data stack
Apache Iceberg, DuckDB, Apache Airflow

Knowledge sharing

I give workshops, training sessions and inspiration sessions at housing associations and healthcare institutions, and guest lectures and knowledge sessions at Tilburg University, Zuyd University of Applied Sciences, Fontys University of Applied Sciences and CorporatiePlein.

  • Data science in practice
  • Data strategy and data-driven working
  • Optimising with process mining
  • Governance and control over data quality
  • Design thinking and successful experimentation

Would you like a session for your organisation? Feel free to get in touch.

Let's meet?

Ready to work with data or AI, but not yet sure where to start? In a one-hour introductory conversation we explore your question, free of charge.