Visivo

Abstract

1. Introduction

Built with by Visivo – a team that's experienced scaling analytics at companies like Intuit, Boeing, and Root Insurance.

We believe data tools should be as reliable as the rest of your tech stack. That's why we built Visivo to bring software engineering best practices to business intelligence.

Watch the Demo Video – See how to build dashboards with Visivo in just a few minutes

2. Objective

✨ Build dashboards with end-to-end version control. 🔋 CLI w/ batteries included, no infra required. Develop on your laptop for instant results, deploy changes safely (with automated checks), and keep every report trustworthy for stakeholders, analysts and agents 🤖

This project demonstrates how JavaScript, Python, React can be applied to a real-world Data Science problem.

4. Technology Stack

5. System Requirements

General requirements for this technology stack — check the README for exact versions.

• Node.js (LTS) and npm
• A modern web browser
• VS Code or any code editor
• Python 3.8 or later
• pip / virtualenv for dependencies
• VS Code, PyCharm or Jupyter Notebook
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/visivo-io/visivo.git
cd visivo

# Install Visivo (works on Mac, Linux, and Windows)
curl -fsSL https://visivo.sh | bash

# Create your first project
visivo init my-dashboard

# Start the development server
cd my-dashboard && visivo serve

# Open http://localhost:8000 in your browser 🎉

# Install and start in one go
curl -fsSL https://visivo.sh | bash
visivo serve --project-dir my-dashboard

# Follow the setup wizard in your browser at http://localhost:8000

pip install visivo

# Install version 1.0.64
curl -fsSL https://visivo.sh | bash -s -- --version 1.0.64

# Or install beta version via pip
python -m pip install git+https://github.com/visivo-io/visivo.git@v1.1.0-beta-1

Full setup instructions are in the project README.

7. Future Enhancements

Suggested extensions you can add to make this your own project.

• Turn the analysis into an interactive dashboard
• Automate data refresh with a scheduled job
• Add a predictive model on top of the analysis

8. Viva / Review Questions

Common questions examiners ask for projects in this domain.

1. What is the source of the dataset and how was missing data handled?
2. Which exploratory analysis steps revealed the most useful insight?
3. Why were these particular charts chosen to present the data?
4. Which statistical or ML technique supports the conclusions?
5. How could the analysis be automated or refreshed with new data?

9. Source Code & License

This project is developed by visivo-io and published on GitHub under the GNU General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.