Databazel

Abstract

1. Introduction

Databazel natively connects to MongoDB and present the results in a visual dashboard reporting interface, without requiring any additional development on your end.

No ETL. We believe you should keep data where it is and use tools that are smart enough to visualize data directly from MongoDB without building ETL.

Our solution is completely web-based so all you need to get started is a web browser!

2. Objective

The analytical and reporting solution for MongoDB

This project demonstrates how JavaScript, Node.js, 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
• Git (to clone the repository)

6. Installation & Setup

git clone https://github.com/apiko-dev/Databazel.git
cd Databazel

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 apiko-dev and published on GitHub under the GNU Affero General Public License v3.0. Please follow the license terms and credit the original author when you use or modify this code.