Data & Analytics
Enterprise Analytics Dashboard
The problem
What this kind of product has to solve
Most analytics projects produce more charts than decisions. A dashboard shows forty metrics because forty were available, each team reads a different number as authoritative, and nobody can tell how stale any of it is.
The failure is upstream of the visualization. Without agreed metric definitions and tested pipelines, a prettier chart just communicates an unreliable number more persuasively.
The solution concept
How we built it
This concept build starts from the decisions rather than the data. Each view answers one question, with the metrics that inform it and nothing else, and the full detail available a click away rather than crowded onto the summary.
Every number carries its definition and the time it was last refreshed. Hovering a metric reveals how it is calculated and which source it derives from, which ends the recurring meeting about whose figure is right.
Charts are built to be read without relying on color alone: direct labeling, distinguishable shapes and dash patterns, a visible tabular view of the same data, and keyboard-reachable tooltips. Drill-through goes to the underlying records, so a surprising number can be investigated rather than merely disbelieved.
Engineering decisions
The choices that actually determine whether it works
- 01
A metric layer, defined once
Definitions live in version-controlled transformations, not in each dashboard query, so every surface reads the same number from the same place.
- 02
Freshness is part of the number
Each panel shows when its data last updated and flags staleness, because a confident chart built on a broken pipeline is the most expensive failure mode in analytics.
- 03
Accessible by construction
No information conveyed by color alone, a data table behind every chart, and full keyboard operation - which also makes the dashboard usable on a projector in a bright room.
- 04
Data tests gate the pipeline
Freshness, row-count variance, uniqueness, and range assertions run on every refresh. A failed assertion raises an alert instead of publishing a wrong figure.
Intended business value
What this is designed to achieve
- Intended to replace recurring disagreements about metric definitions with a single documented source, so meetings start from the decision rather than the reconciliation.
- Designed to make pipeline failure visible rather than silent, which is the difference between a dashboard people trust and one they quietly stop opening.
- Built so that analysts extend the shared model instead of forking new queries, keeping definitions consistent as reporting needs grow.
No outcome figures are shown because this is a concept build with no client deployment behind it. Quoting a percentage here would be fabrication, so we quote nothing.
Built with
- Next.js
- TypeScript
- PostgreSQL
- dbt
- SQL
- Server-side rendering
- Accessible SVG charts
Interface rendered from styled markup rather than a screenshot - crisp at any density, and no image request. Values shown are illustrative.
Related
Services and sectors this relates to
- ServiceData Engineering & AnalyticsPipelines, warehouses, and dashboards that produce one trusted number instead of four plausible ones - with tests on the data itself.Read more
- ServiceUI/UX & Product DesignResearch, interface design, and design systems - the work that decides whether people can actually complete the task your software exists to support.Read more
- ServiceCloud, DevOps & InfrastructureArchitecture, pipelines, and observability that make deployment routine - plus the cost visibility that stops a cloud bill from becoming a surprise.Read more
- IndustryFinancial Services & FintechSystems where correctness is not negotiable, reconciliation is a first-class feature, and every number must be traceable.Read more
- IndustryLogistics & Supply ChainOperations that run in real time across many parties, where data arrives late, incomplete, and occasionally contradictory.Read more
- IndustryOperations-Heavy BusinessesManufacturers, service networks, field teams, and distributors where the real process lives in spreadsheets nobody documented.Read more
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