The data model is the product. A Model Citizen builds it right.
Model Citizen provides content, resources and contract services for data analysts, engineers and leaders who treat the semantic model as the spine — the one layer that analytics and AI are both built to stand on.
Define it once. Trust it everywhere.
Skim for the idea that matches what you're wrestling with right now — each one's a short, field-tested read that connects straight through to the real work it came from.
Grounding Is the New Formatting
For a decade the craft that set a report apart was formatting. Now it's grounding — the descriptions and synonyms that tell an agent what a number actually means. Same instinct, higher stakes.
Scan the cards below for the symptom that sounds like yours — each one spells out what's actually going on and what to do next, whether that's a fix you can run yourself or a conversation worth having.
“The bill keeps climbing and no one can say why.”
Bottlenecks, runaway compute, and silent risks hiding in a stack nobody's audited end to end.
“Every dashboard tells a different number.”
No trusted model underneath. "Revenue" is defined ad hoc in five places, so five reports disagree.
Or maybe it's one of these
Grab what's useful — templates, guides, and tools I've built and actually used, free to download, no email required.
Implementing Your Own Data Concierge
A scoping guide for the Data Concierge methodology — the 5-phase build sequence, the staged rollout pattern, and a self-assessment to gauge your own scope before a scoping call.
Download ↓Data Quality Scorecard
A weighted scorecard to grade any table on freshness, completeness, validity, consistency, and uniqueness — with a scoring rubric on the second tab.
Download ↓See what's actually been built — real use cases and working prototypes, browsable by the outcome they drive, not just the tech underneath.
The Data Concierge, Deployed
From Ticket Queue to a Tool 200 People Open Daily
Attributing Friction, Not Blame
Have data that should be doing more?
Tell me about the pipeline that breaks, the metric nobody trusts, or the analysis stuck in a notebook. Let's operationalize it.