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kpi-dashboard-design

Design KPI dashboards with SQL and Python Streamlit code.

Updated May 31, 2026
Search Tags:#data visualization#business intelligence#real-time monitoring#executive reporting#metric design#KPI dashboard#dashboard creation
One-click install
npx skills add https://github.com/sebach0/SEGUNDO-EXAMEN-PARCIAL-APP.-WEB-Y-MOVIL --skill kpi-dashboard-design-sebach0
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: kpi-dashboard-design
Source: https://github.com/sebach0/SEGUNDO-EXAMEN-PARCIAL-APP.-WEB-Y-MOVIL/tree/main/.agents/skills/kpi-dashboard-design
Command: npx skills add https://github.com/sebach0/SEGUNDO-EXAMEN-PARCIAL-APP.-WEB-Y-MOVIL --skill kpi-dashboard-design-sebach0

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill addresses the challenge of designing effective KPI dashboards that clearly present complex metrics for informed business decisions, real-time monitoring, and department-specific views.

Core Features & Use Cases

  • KPI Framework & Metrics Selection: Establishes a comprehensive KPI framework, guiding the selection of meaningful metrics aligned with strategic, tactical, and operational levels.
  • Dashboard Hierarchy: Outlines dashboard hierarchy with executive summaries, departmental views, and detailed drilldowns.
  • Implementation Patterns: Provides patterns for executive summary, SaaS metrics dashboard, and real-time operations dashboards.
  • SQL for KPI Calculations: Demonstrates SQL queries for calculating monthly recurring revenue (MRR), cohort retention, and customer acquisition cost (CAC).
  • Python Dashboard Code (Streamlit): Includes example Python code using Streamlit to create a KPI dashboard with charts and data visualization.

Quick Start

Utilize the 'kpi-dashboard-design' skill to design an executive KPI dashboard tracking revenue growth and churn rate. Execute the SQL script for calculating MRR and retention and implement the Python Streamlit dashboard code.

Frequently Asked Questions about kpi-dashboard-design

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I design a KPI dashboard for executive reporting and real-time monitoring?▼

To design a KPI dashboard, establish a metric framework aligned with strategic goals, outline a dashboard hierarchy from executive summaries to drilldowns, and implement visualization patterns using SQL for calculations and Python with Streamlit.

What metrics should I include in a SaaS KPI dashboard?▼

A SaaS KPI dashboard should include metrics like monthly recurring revenue (MRR), cohort retention, and customer acquisition cost (CAC), selected by aligning them with strategic, tactical, and operational levels for comprehensive performance tracking.

How do I calculate MRR and cohort retention using SQL for business intelligence?▼

Calculating MRR and cohort retention using SQL involves executing specific query patterns that aggregate subscription revenue and track customer behavior over time to provide accurate data for your KPI dashboard.

Can I use Python and Streamlit to create a real-time operations dashboard?▼

Yes, you can use Python with Streamlit to create a real-time operations dashboard by implementing the provided example code, which generates interactive charts and data visualizations for live business performance tracking.

What is the best way to structure dashboard hierarchy for department-specific views?▼

The best way to structure dashboard hierarchy is to build layered views starting with an executive summary, branching into departmental views, and ending with detailed drilldowns for focused metric analysis.

Do I need a metric framework before building a KPI dashboard?▼

Yes, establishing a KPI framework is necessary before building a dashboard to ensure the selected metrics are meaningful, correctly aligned with business objectives, and effectively support data visualization and decision-making.

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