Corporate Data Department System
A data team managing the company's sources, models, executive dashboards, and analysis requests.
From connecting a source to delivering an analysis — with unified metric definitions and data quality fixed at the source.
No credit card required — your project is set up with the full system in under a minute
This is the system board as you'll receive it: workflow columns and starter cards showing the first steps
How does work flow in this system?
Work starts at “Source”: a card for every new data source — a sales system, a marketing platform, operational spreadsheets — documenting the access method, source owner, and update frequency. Data moves to “Model,” where data engineers build unified tables and relationships; then to “Dashboard,” turning it into scoreboards that serve management decisions. Data quality is managed on separate cards in “Quality”: missing, duplicate, and conflicting data problems are fixed at their source, not by cosmetically adjusting numbers. Management's analysis requests enter “Analysis Request,” are picked up by analysts, and end in “Delivery” with a report or dashboard handed to its requester with documented assumptions.
Chat is for daily coordination between analysts and engineers, and for quick definition questions with departments. The Forum documents the metric definition dictionary — the official definition of “revenue” and “active customer” and how each is calculated — and data governance decisions, so definitions don't multiply across departments and reports don't conflict. Dues records data tool, storage, and cloud service subscriptions, reviewed at every renewal.
Data engineers prepare sources and build models; analysts build dashboards and answer analysis requests; and the data manager approves metric definitions in the Forum, reviews “Quality” cards weekly, and receives management requests and distributes them among analysts by specialty and workload.
Who does what?
The operational roles in this system and each role's responsibility in daily work — assign them to your team as-is or adapt them to your reality.
Data Manager
Approves unified metric definitions in the Forum, triages and assigns incoming analysis requests, and reviews “Quality” cards weekly.
Data Engineers
Connect sources and build unified models, fixing quality problems at the source in coordination with the data-owning departments.
Data Analysts
Build dashboards and answer analysis requests, delivering them to their owners in “Delivery” with assumptions and sources documented.
What's prepared for you from day one?
System units
- Tasks — A kanban board with workflow columns and execution cards
- Chat — The team's fast daily coordination channel
- Forum — Documented discussions in organized sections — decisions and knowledge that never get lost
- Dues — Internal money with strict privacy — dues, advances, and expenses
Forum sections (3)
- Metrics & Definitions DictionaryThe official approved definition of every company metric: how it's calculated, where it's pulled from, and who owns it.
- Data GovernanceDecisions on data access, ownership, retention, and confidentiality — the authority invoked for any new access request.
- Recurring Quality IssuesRoot-cause analysis of recurring data problems and agreeing to fix them at the source with the owning departments.
«Working Rules for This System» — Pinned in the forum
1. No metric is shown to management before its definition is approved in the “Metrics & Definitions Dictionary.” 2. Every data source has its owner and update frequency documented on its card before being connected. 3. A quality problem is fixed at its source, not on the dashboard — cosmetic number-touch-ups are forbidden. 4. Every analysis request is delivered with its assumptions and sources documented on the card. 5. Data tool subscriptions are recorded in Dues and their value reviewed at every renewal.
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