Dashboard Design Guidelines
Program Information
- 🎓 Delivery Method:
- On-site (available now, on demand)
- Remote (live, on demand)
- Online (self-paced, coming soon)
- ⏳ Duration:
- 3 days, 4 hours per day
- Custom options available for internal teams
- 🧩 Format:
- Interactive workshops
- Hands-on exercises
- 👨🎓 Maximum Participants:
- 12 per session (to ensure personalized interaction)
- 📋 Course Requirements:
- No prior technical background required.
- 📅 Scheduling:
- Flexible scheduling available on demand
- 📞 Contact to Schedule:
- 📧 training@vizacta.com
Course Description
Want to build dashboards that truly inform, influence, and drive decisions — not just display data?
This hands-on course will walk you through the entire process of designing clear, impactful business dashboards from scratch. Whether you’re a data analyst, BI developer, designer, or product owner, you’ll learn exactly how to turn raw data and stakeholder needs into high-performing dashboards that users actually love and use.
We’ll skip the fluff and focus on practical design principles and techniques used by top professionals — inspired by the work of Stephen Few, Nicolas Desbarats, and Cole Nussbaumer Knaflic. Each module is a critical step in the dashboard design journey, with real-world examples, makeovers, and hands-on exercises to apply what you learn immediately.
What you will learn
- How to define the right purpose, audience, and KPIs
- Layout techniques that guide attention and reduce clutter
- Which chart types work best — and which ones to avoid
- How to use color, typography, and spacing for clarity
- Labeling, iconography, and storytelling strategies that make insights pop
- How to bring it all together into a polished, professional dashboard
- Final fine-tuning before going live
Course Content
- Define the user: executive, manager, analyst?
- Identify dashboard type: operational, strategic, analytical
- Clarify goals and decisions the dashboard will support
- Avoid “data-dump” dashboards — focus on actionable insights
- Determine update frequency: real-time, daily, weekly, monthly
Outcome: A clear dashboard design brief with purpose, audience, and KPIs.
- Use F-pattern or Z-pattern layout to guide visual flow
- Zone your layout: KPIs at the top, trends in the middle, details at the bottom
- Group related charts with proximity and white space (not borders)
- Minimize containers and grid clutter
- Create a rough wireframe before building in a tool
Outcome: A wireframed layout that supports scanning and prioritization.
- Match chart to question type: comparison, trend, distribution, correlation, composition
- Prefer bar charts for comparisons, line charts for trends, scatterplots for relationships
- Avoid pie charts, donut charts, 3D charts, and gauges
- Use small multiples for consistent comparisons
- Only include tables when precise values are required
Outcome: A set of clear, well-matched chart types for each data story.
- Apply color intentionally — not as decoration
- Use color types correctly: categorical (hues), sequential (light to dark), diverging (2-hue)
- Designate one highlight color for alerts or key metrics
- Avoid rainbow palettes and overuse of color
- Ensure accessibility with colorblind-safe palettes (e.g. ColorBrewer)
Outcome: A consistent and effective color scheme that reinforces meaning.
- Use 1–2 clean sans-serif fonts for clarity (e.g. Inter, Roboto)
- Establish font hierarchy: titles (18–24pt), labels (10–12pt), notes (9–10pt)
- Format numbers consistently: use K/M, decimals, % as needed
- Align text with visuals; right-align numeric columns
- Avoid ALL CAPS and decorative fonts
Outcome: Text elements that are easy to read, scan, and interpret.
- Use direct labeling on charts instead of legends
- Annotate trends, outliers, or comparisons with short notes
- Add sparing iconography: arrows, checkmarks, status dots
- Include benchmark references: vs. target, goal, last month
- Use microcharts (sparklines, bullets) for context at a glance
Outcome: Dashboards that explain themselves and reduce misinterpretation.
- Align all elements to a layout grid — avoid visual drift
- Ensure equal padding and spacing between sections
- Standardize chart settings: same line weight, bar thickness, axis formatting
- Use a consistent icon and visual vocabulary across the dashboard
- Ensure visual hierarchy supports top-down comprehension
Outcome: A polished, cohesive dashboard with a professional finish.
- Eliminate chart junk: 3D effects, shadows, bold gridlines
- Validate data clarity — are the takeaways obvious?
- Test readability across screen sizes (laptop, monitor, tablet)
- Gather user feedback on usefulness and ease of use
- Use a final QA checklist to ensure everything works and communicates clearly
Outcome: A final, production-ready dashboard ready to deploy or present.