Unifying Business, Data, and Code: Designing Data Products with JSON Schema

From Misalignment to a Shared Design System

Most organizations collect plenty of data, yet still struggle to turn that data into products that teams actually understand and trust. Unifying Business, Data, and Code attacks that problem at its source: the silent misalignment between business stakeholders, data specialists, and engineers. Ron Itelman and Juan Cruz Viotti use JSON Schema as the connective tissue, showing how a formal, shared vocabulary can remove ambiguity and assumptions that slow down innovation.

The Four Facets of a Data Product

The book centers on a practical blueprint: every data product can be described through data, structure, meaning, and context. By making these facets explicit, teams stop guessing about what a dataset represents and start agreeing on a single source of truth. The authors walk through concept-first design, where you map out the conceptual terrain before writing a single line of code.

• Concept compass – locate the biggest sources of misalignment in your organization
• Success spectrums – define the knowledge and milestones needed to reach your goal
• Data hygiene – design high-quality datasets that protect business value
• JSON Schema in practice – validate data, extract annotations, and host your own schema registry

Practical Tools for Data Champions

Early chapters introduce JSON as the lingua franca of data and JSON Schema as the rules that give data real meaning. You’ll learn how to build schemas step by step, use annotations to encode business logic, and extend JSON Schema with custom keywords. Later chapters cover deployment with GitHub and Cloudflare Pages, showing how to make schemas immutable and versioned.

Bringing Knowledge and Governance Together

The authors also explore knowledge graphs and CLEAN data governance—collaboration, knowledge, business logic, activity—to help teams think in networks rather than silos. Real-world examples, such as a coffee bean analytics project, keep the ideas grounded. The result is a methodology that unifies people, processes, and technology around data products that everyone can understand.

Whether you’re a data product manager trying to align stakeholders, an engineer building data platforms, or a business leader tired of data project failures, this book gives you a common language to move forward together.