How a conference, a few books, and a single meeting reshaped my approach to data and collaboration.
Summary
This is a reflection on how Steve Hoberman’s work — in his books, his publishing, and through the Data Modeling Zone (DMZ) conferences — has influenced my data modeling career.
I share how meeting like-minded peers (such as Hans Hultgren), learning new methodologies (especially The Data Model Scorecard), and participating in DMZ molded my ideas, practices, and professional network. I also look ahead to the next conference and how it offers new opportunities to grow.
When I look back on my journey in data, a few names stand out as turning points. One of those names is Steve Hoberman.
Steve has been a guiding force in the world of data modeling for decades. Through his own books, his teaching, and his publishing work under Technics Publications, he has helped create a shared language for data professionals. But what really sets him apart is his commitment to building a community around data modeling — a community that gave me some of the most important milestones in my own professional journey.
The Books That Set the Stage
Steve is well known for Data Modeling Made Simple: A Practical Guide for Business & IT Professionals, a book that many turn to for getting started and for cleaving through the complexity of the modeling discipline.
Another essential work of his is The Data Model Scorecard: Applying the Industry Standard on Data Model Quality (2015, Technics Publications). This is more than just a book — it’s a methodology. The Scorecard defines ten categories for assessing models: Correctness, Completeness, Scheme, Structure, Abstraction, Standards, Readability, Definitions, Consistency, and Data. It gives modelers a way to measure model quality, spot gaps, and systematically improve their models.
He has also published (or co-published) other useful books via Technics Publications, including Data Modeling for the Business: A Handbook for Aligning the Business with IT Using High-Level Data Models, The Rosedata Stone: Achieving a Common Business Language using the Business Terms Model, Data Modeling Master Class Training Manual, and more. These works provide both foundational and advanced tools for modeling in practice.
While foundational works by other authors — such as Len Silverston’s The Data Model Resource Book or Hans Hultgren’s Modeling the Agile Data Warehouse with Data Vault — continue to influence me, Steve’s publications have given me tools I can apply directly day to day.
The Power of Data Modeling Zone
One of the defining points in my growth came from attending Data Modeling Zone (DMZ), the conference series Steve chairs. Held in both Europe and the U.S., DMZ is more than just sessions — it’s a space for dialogue, mentorship, experimentation, and building relationships with others who care deeply about modeling.
At a DMZ in Europe, I met Hans Hultgren. That connection opened up new perspectives around Data Vault, ensemble modeling, and how to think more flexibly about evolving data architecture. It shifted how I view modeling not just as technical design, but as a collaborative, communicative, and continuously improving discipline.
A Key Work: The Data Model Scorecard
One of Steve Hoberman’s most important contributions is The Data Model Scorecard: Applying the Industry Standard on Data Model Quality. Here are some ways I plan to explore integrating the Scorecard methodology into our modeling practice:
- Embedding the Scorecard into peer-review practices so each new or revised model is scored using the ten criteria.
- Including it as part of quality gates in your development workflow — before moving from logical to physical, or prior to deployment.
- Using it as a training tool: run review workshops where team members score models together, so there’s a shared sense of what “good quality” looks like.
- Periodically benchmarking existing models against the Scorecard to highlight areas for refactoring or improvement.
I’m planning a future article diving into exactly how our team can adopt these ideas in practice — how we institutionalize them, measure progress, and make them part of our way of working.
Why This Still Matters
Today, the world of data is more dynamic than ever: evolving tools, emerging AI, streaming data, data contracts, semantic layers, and more. In this context:
- Community helps you stay current and grounded. The chance to share lessons, try new patterns, and get feedback — not just read theory — is invaluable.
- Model quality becomes critical when many people, tools, and systems depend on data being defined, consistent, and meaningful. Steve’s Scorecard works as a kind of compass.
- People and meetings matter. A single conversation with a thoughtful peer, at a conference like DMZ, can trigger ideas or shifts that you carry forward for years.
Looking Ahead: DMZ 2026
Here’s what’s coming up and what I’m excited about:
- Dates & Location: DMZ 2026 will take place March 3–5, 2026, at the Oracle Conference Center in Redwood City, California, in the heart of Silicon Valley. technicspub.com
- Format: Three days — one day of pre-conference workshops + two main days of sessions. technicspub.com
- Tracks & Sessions: Over 60 sessions across tracks such as Foundational Modeling Skills, Intermediate/Advanced Modeling & Case Studies, DMBOK/CDMP, AI/Semantics, and Communication. technicspub.com
- What to Expect: Hands-on workshops (including ones Steve leads), real case studies, peer networking, and sessions that will challenge and extend your modeling approach. For me, it’s a chance to test ideas from The Data Model Scorecard, engage with peers, and return with renewed energy and tools.
Key Takeaways
✨ If you’re a data professional (or just starting out), I encourage you to pick up one or two of Steve’s books — especially The Data Model Scorecard — and plan to attend the next Data Modeling Zone.
✨It’s an investment not just in ideas, but in the people who share them — and those connections often make the difference.