About binom-tools
Governance help hub for orientation, questions, tools, and evidence — by Thomas Lindackers.
What is binom-tools?
binom-tools is an open-source project by Thomas Lindackers: a usable governance help hub with Markdown stories and interactive reference workflows — not a commercial product and not legal advice.
Stories
The playbooks offer a general introduction to governance and the worlds around it — from data platforms and BI to processes and the topics that matter in practice. It is knowledge collected over the years: experience, models, and ideas to explore, not a finished handbook.
Why governance?
Data governance starts with practical decisions: which stack, which source, which KPI grain, which PII controls. Binom Governance is a help hub by Thomas Lindackers — orientation first, then tools and evidence — not a vendor directory and not legal advice.
Signature models
Decision Ladder
Decision Ladder: orientation → questions → tools → evidence. Entry is the Governance Advisor — not another decision page.
Collect Infos 8
Collect Infos 8 is the named scaffold for the eight Discovery Canvas steps: from stakeholders and KPI cards through source scope, PII and DQ to mart design brief and decision brief.
Evidence Loop
Evidence Loop: decision → control → evidence. If a piece is missing, the metric stays untrusted — see Missing Pieces of Trusted Metrics.
Platform Starting Point: choose the entry by cloud/BI/catalog fit, not by feature list. Source Load First: load the source that carries owner, grain, and pilot outcome fastest.
The 8 Pillars stay the practical scaffold — DMBOK/CDMP are domain language, not the site structure.
Governance
Interactive reference workflows make ideas from the stories practical — step by step, copy-paste ready for your warehouse or governance setup. Example path: advisor → demo workspace → report.
Visuals
Diagrams and illustrations for playbook examples are created with AI, aligned with a consistent corporate design so stories stay readable and comparable.
Help & tours
Short tours for getting started — platform, learning paths, and Sprint Planner.
Feedback
Feedback, corrections, and improvements are welcome via GitHub issues and pull requests.