SLEGO: A Collaborative Data Analytics System

Overview

SLEGO (Software-Lego) is a cloud-based collaborative analytics platform designed by NG Siu Lung, a PhD student at UNSW's Computer Science and Engineering (CSE) department and the FAIC Research Center. The platform bridges the gap between experienced developers and novice users by leveraging modular, reusable microservices and a graphical user interface (GUI) to enable the creation of comprehensive analytics pipelines without requiring programming skills.

For more detailed information, you can refer to the paper: SLEGO: A Collaborative Data Analytics System.

Features

• Modular Microservices: Easily share and integrate analytical tools and workflows.
• User-Friendly GUI: Create analytics pipelines through a simple drag-and-drop interface.
• LLM-Powered Recommendations: Enhance microservice selection and integration with a knowledge base and recommendation system.
• Collaborative Environment: Promote resource reusability and team collaboration.

Use Cases

• Finance: Streamline financial data analysis with reusable microservices.
• Machine Learning: Simplify the process of building and deploying ML models.
• All other data-intensive applications

Getting Started

1. Installation: Clone the repository and follow the setup instructions.
2. Usage: Use the GUI to start building your analytics pipelines.
3. Documentation: Refer to the detailed documentation for advanced features and customizations.

License

This project is licensed under the Apache-2.0 license. See the LICENSE file for details.

Opening the App on Codespaces (GitHub)

TLDR, just click: https://codespaces.new/alanntl/SLEGO-Project

1. Fork the Repository:

   • Go to the SLEGO repository and fork it to your GitHub account.

2. Open in Codespaces:

   • Once the repository is forked, navigate to the main page of your fork.
   • Click on the green “Code” button, and select “Open with Codespaces”.
   • If you don’t see this option, ensure that you have Codespaces enabled for your GitHub account.

3. Setup the Environment:

   • Codespaces will automatically start setting up your development environment.
   • Follow any additional setup instructions provided in the repository’s documentation.

4. Start Building:

   • Once the setup is complete, use the GUI to start building your analytics pipelines.