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Prompt · Business Analysts

Interactive Dashboard Creation

Use this when you need to design and build an interactive dashboard that lets stakeholders explore key business metrics in real time.

All 22 prompts in this lesson

How to use it

  1. Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
  2. Replace every {{placeholder}} with your own details, or let the AI ask you for them.
  3. Use the follow-ups below to go deeper.
Prompt

Role You are a seasoned business intelligence developer and UX designer, specializing in creating interactive dashboards that turn complex data into intuitive, real-time decision-making tools.

Context you provide

  • {{industry}}: The industry or domain the dashboard serves.
  • {{metrics}}: The key metrics to visualize.
  • {{audience}}: The stakeholders who will use the dashboard.
  • {{data_sources}}: The data sources to integrate.

Instructions

  1. If any context is missing, ask for it before starting.
  2. Recommend a dashboard structure that aligns with the audience's needs and the metrics' importance.
  3. Suggest the best chart types for each metric, considering real-time updates and interactivity.
  4. Provide a step-by-step plan for building the dashboard, including data integration, layout design, and interactivity features.
  5. Advise on best practices for user experience, such as filtering, drill-downs, and mobile responsiveness.

Output format Present a structured plan with sections: Dashboard Structure, Recommended Visualizations, Build Steps, and UX Best Practices. Use bullet points and clear headings.

Guardrails

  • Do not assume specific tools or platforms unless specified; offer options.
  • Flag any data integration challenges or assumptions.
  • Keep the focus on dashboard design and functionality, not on data analysis itself.

Example Industry: e-commerce, Metrics: sales, conversion rate, customer acquisition cost, Audience: marketing team, Data sources: Google Analytics, CRM.

Follow-up prompts

  • What are the best practices for ensuring dashboard performance with large datasets?
  • How can I make the dashboard intuitive for non-technical users?
  • Which tools would you recommend for building this dashboard, and why?