Nodewave

Overview

Nodewave is a data analytics platform, equipped to help you analyze data throughout the entire data analysis process. Nodewave is capable of doing everything from exploratory data analysis to monitoring management metrics.

Project Description

This project was made as a part of Prof. Anand Gupta's Senior Design (CS 4485) section by UTD students.

Installation

To get started with this project, follow these steps:

1. Clone the repository:

   git clone https://github.com/greeshiee/CS4485-T7.git

2. Install Docker on your system if you haven't already. You can download it from the official Docker website. a. Ensure your system meets the requirements:

   • For Windows: 64-bit Windows 10 Pro or higher
   • For macOS: macOS 10.14 or newer
   • For Linux: A supported Linux distribution (e.g., Ubuntu, Debian, CentOS)

   b. Download Docker Desktop from the official Docker website (https://www.docker.com/products/docker-desktop).

   c. Run the installer:

   • On Windows: Double-click the Docker Desktop Installer.exe
   • On macOS: Drag the Docker icon to the Applications folder

   d. Follow the installation wizard:

   • On Windows, ensure "Use WSL 2 instead of Hyper-V" is selected if available
   • Accept the license agreement

   e. After installation, start Docker Desktop:

   • On Windows and macOS: Open Docker Desktop from the Start menu or Applications folder
   • On Linux: Start the Docker service with sudo service docker start

   f. Verify the installation by running:

   docker --version
   docker run hello-world

Usage

3. Set up and run the Mage data pipeline:

   cd mage-t4
   docker compose up

4. Start the backend:

   • On Windows:

     cd api
     start_api.bat
     

   • On macOS/Linux:

     cd api
     ./start_api.sh
     

5. Run the frontend:

   npm start

Note each of these must be run on a separate terminal, all these processs are mean to be executed concurrently.

Features

Nodewave offers a comprehensive suite of data analytics tools and functionalities:

• Data Pipelining: Efficiently manage and automate your data workflows.
• Fault Management: Monitor and handle system faults through a dedicated interface.
• Data Ingestion: Seamlessly import data from various sources into the platform.
• Performance Management: Track and analyze system performance metrics.
• Authentication: Secure user authentication system to protect sensitive data.
• KPI Formula Management: Define and manage Key Performance Indicators for your data.

Each of these components contributes to making Nodewave a powerful and versatile data analytics platform, capable of handling complex data processing tasks and providing valuable insights.