Prompt · Process Improvement Analysts
Interactive Dashboard Development
Use this when you need to develop an interactive dashboard that integrates multiple data sources for comprehensive efficiency tracking.
How to use it
- Copy the prompt and paste it into ChatGPT, Claude, Gemini or any other AI.
- Replace every {{placeholder}} with your own details, or let the AI ask you for them.
- Use the follow-ups below to go deeper.
Role You are a dashboard developer and data analyst. Your objective is to create a prototype for an interactive dashboard that integrates data from multiple sources, visualizes efficiency metrics, and supports drill-down analysis for decision-making.
Context you provide
- {{data_sources}}: The systems or databases to integrate (e.g., production systems, CRM, ERP).
- {{metrics}}: The efficiency metrics to visualize (e.g., throughput, downtime, cost per unit).
- {{user_needs}}: The specific needs of the users (e.g., drill-down by region, time period, product line).
- {{tech_stack}}: The preferred technology or tools (e.g., Power BI, Tableau, custom web app).
Instructions
- Request missing inputs if not provided.
- Analyze the {{data_sources}} to understand data structure and integration points.
- Design an interactive dashboard that aggregates data from all sources and displays the {{metrics}} clearly.
- Include drill-down capabilities (e.g., from summary to detail views) based on {{user_needs}}.
- Ensure the dashboard is customizable (e.g., filters, date ranges, user-specific views).
- Provide a prototype description or wireframe, and suggest how to handle real-time data updates.
Output format Deliver a development plan with sections: Data Integration Strategy, Dashboard Features, Interactivity & Drill-Down Design, Technology Recommendations, and Prototype Overview. Use bullet points and a clear structure. Tone should be technical yet accessible.
Guardrails
- Do not assume data availability or structure; base on provided sources.
- Flag any technical limitations or assumptions about the tech stack.
- Keep the design aligned with the specified metrics and user needs.
Example
- {{data_sources}}: Production system (SQL), CRM (API), {{metrics}}: cycle time, defect rate, {{user_needs}}: drill-down by plant and shift, {{tech_stack}}: Power BI.
Follow-up prompts
- What are the best practices for handling data latency in real-time dashboards?
- How can we ensure the dashboard scales with more data sources?
- What user training would be needed for effective adoption?