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A copy for your desk, your bag, and your next difficult modeling conversation.
Purchase hereJOE REIS · BOOK 1
Mixed
Model Arts.
The Building Blocks of
Cross-Disciplinary Data Modeling
Real-world data doesn't stay in one discipline.
Your thinking shouldn't either.
Foreword by Bill Inmon
FIVE DISCIPLINES. A BROADER PERSPECTIVE.
RELATIONAL / ANALYTICS / APPLICATIONS / ML/AI / KNOWLEDGE
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BEYOND A SINGLE SCHOOL OF THOUGHT
Data modeling is having
its UFC moment.
Every discipline has its strengths. Every discipline has its blind spots. Real-world problems don't care which camp you belong to.
Mixed Model Arts brings the major schools of data modeling into the same conversation. Learn to see what they share, where they differ, and how to draw from each with intention.
For data engineers, architects, analysts, and anyone making decisions about how data represents the world.
WIDEN YOUR REPERTOIRE
Five camps.
One real world.
Explore the perspectives.
Find the connections.
STRUCTURE & INTEGRITY
What must be true
about your data?
Entities, relationships, keys, and constraints. Relational thinking gives you a disciplined way to express structure and protect the integrity of your data.
The connection: identity and relationships matter in every model.
BUILD YOUR FOUNDATION
Tools change.
The hard questions
remain.
01 / REPRESENTATION
What are you modeling?
Entities, attributes, and relationships. The choices that shape how a system sees the world.
02 / CONTEXT
What does it mean?
Grain, time, and meaning. Make the assumptions behind a model explicit.
03 / PRACTICE
How does it hold up?
Organizational realities, trade-offs, and the ongoing work of keeping models useful.
PUT IT INTO PRACTICE
The real work
happens in the gym.
Start with the foundations.
Build your own approach.
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