RevOps Control Center

A modern, responsive analytics dashboard for revenue operations teams. Visualize marketing, pipeline, and revenue data with interactive filters, beautiful charts, and actionable insights—all powered by local CSVs and Python.

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Architecture Overview

• Streamlit UI: streamlit_app/app.py — main dashboard, filters, and theming
• Analytics Layer: src/revops/analytics/ — KPI calculations and aggregations
• Data Access: src/revops/data.py — cached CSV loaders
• Synthetic Data: src/revops/data_generation.py — CLI to generate demo datasets
• Validation: src/revops/validation.py — schema checks for all data
• Tests: tests/ — pytest suite for analytics and validation

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Quick Start: Run in 5 Minutes

1. Clone and enter the repo

   git clone <your-fork-url> revops-dashboard
   cd revops-dashboard

2. Create a virtual environment and install dependencies

   python3 -m venv .venv
   source .venv/bin/activate
   pip install -e '.[dev]'

3. (Optional) Regenerate demo data

   python -m revops.data_generation --output .

4. Launch the dashboard

   streamlit run streamlit_app/app.py

5. Open your browser
   • Go to http://localhost:8501
   • Explore tabs for Marketing, Pipeline, Revenue, and Insights

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Seed Data

• marketing_channels.csv — marketing funnel events
• pipeline_deals.csv — sales pipeline deals
• revenue_customers.csv — customer revenue and churn
• benchmarks.csv — industry targets for KPIs

Regenerate all with:

python -m revops.data_generation --output .

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Project Structure

streamlit_app/         # UI, theming, entrypoint
src/revops/            # Analytics, data, validation, generation
  analytics/           # KPI logic
  ai/                  # Insights engine
  data.py              # CSV loaders
  data_generation.py   # Synthetic data CLI
  validation.py        # Schema checks
  config.py            # Data paths
benchmarks.csv         # Seed data
marketing_channels.csv # Seed data
pipeline_deals.csv     # Seed data
revenue_customers.csv  # Seed data
tests/                 # Pytest suite
README.md              # This file

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Setup Scripts

• Install: pip install -e '.[dev]'
• Generate data: python -m revops.data_generation --output .
• Run tests: pytest
• Start dashboard: streamlit run streamlit_app/app.py

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Documentation

• docs/developer-guide.md — technical deep dive
• docs/business-user-guide.md — user-facing walkthrough

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License

MIT (see LICENSE)