A practical library for data and AI judgement.
The Field Guides explain how we think about serious data work: how to frame problems, evaluate options, make trade-offs, and turn principles into systems that can be built, governed and trusted.
A reference for judgement, not doctrine.
The Field Guides are where we make our working method explicit. They are written for leaders, architects and practitioners who need to make better decisions about data systems, analytical tools, governance, AI and the operating work around them.
They are not vendor playbooks or abstract thought pieces. Each guide is meant to help a team understand the problem in front of them, see the trade-offs, ask sharper questions and choose a practical next step.
Start with the situation.
Use the guides from the problem you are facing: an operating pain, architecture decision, governance gap, delivery risk or capability question.
Prefer principles before patterns.
Patterns are useful only when the assumptions are visible. The guides explain where a pattern fits, where it fails and what it costs to operate.
Make trade-offs explicit.
Good technical decisions are not made by popularity. They depend on risk, constraints, team capability, business value and the cost of being wrong.
Turn knowledge into action.
The guides should lead to useful artefacts: clearer requirements, stronger designs, better assessments, simpler roadmaps and systems people can trust.
Available field guides.
Chart Design
A practical guide to choosing, designing and reading charts, with a taxonomy of chart types and principles for making visual evidence easier to understand.
OPEN GUIDE →COMING SOONThe Data Leader's Field Guide
A practical field guide for data leaders is in development. It will be published once the structure, examples and guidance are ready.
VIEW STATUS →Assessments
Interactive tools for data maturity, AI readiness and architecture review.