Well-organized panels make analytics easier to understand, share, and act upon. This guide explains how to structure Observatory panels so dashboards remain clear, focused, and useful as your data grows.
Create panels based on what problem the dashboard is solving.
Each panel should answer a specific question.
Different stakeholders care about different metrics. Design panels accordingly.
Audience-focused panels reduce noise and improve adoption.
Time-based panels help track progress and trends.
These panels are ideal for recurring reviews and reporting.
When projects are large, feature-level panels provide clarity.
This approach works well for component-based ownership.
Define the Goal First
Decide what insight the panel should provide before creating it.
Use Clear Titles
Titles should reflect what the panel answers, not just what it contains.
Add Descriptions
A short description helps others understand the intent of the dashboard.
Start Small
Begin with a few key charts and expand only when needed.
Review Panels Regularly
Retire panels that are no longer relevant.
Keep Descriptions Updated
Ensure descriptions still match the panel’s purpose.
Avoid Duplicate Panels
Consolidate similar dashboards where possible.
Organize Consistently
Follow the same organizational logic across projects.
Limit Scope
Each panel should focus on a single theme or question.
Design for the Viewer
Optimize panels for the intended audience.
Use Naming Conventions
Consistent naming improves discoverability.
Avoid Overloading
Too many metrics reduce clarity and impact.
Limit Charts per Panel
5–10 charts per panel is a good guideline.
Group Related Charts
Place related metrics near each other.
Maintain Logical Flow
Arrange charts in a top-to-bottom narrative (overview → details).
Review Chart Relevance
Remove charts that no longer provide value.
Purpose
Track release readiness and quality.
Typical Charts
Audience
Release managers, QA leads
Purpose
Monitor ongoing execution health.
Typical Charts
Audience
QA team, test managers
Purpose
Understand test case composition and gaps.
Typical Charts
Audience
Test architects, automation engineers
Purpose
Track validation coverage for requirements.
Typical Charts
Audience
Product owners, business analysts
Well-structured panels turn analytics into actionable insights.