If you are open this repository in PSU GitLab Version - it's open access to all PSU but I have to hide some of personal or commercial data and resulting output or I will show you as demonstration data instead but the trend of data is a lot different compare to the original. You can see the full version of repository with data if you have access credential for IARC-Programing Github Private Repository. Or for educational purpose you can contact me.

Visit Open Source Version of this project (with some hide and no credential) at de-final PSU GitLab

1. Data Cleansing and manuipulation using Pandas on Python Notebook notebooks/Notebook1.ipynb
2. Inserting to MariaDB database
3. Fetching in Microsoft PowerBI and Create the Dashboard dashboard-ssp.pbix

For in Private Repository Version you can visit photo at unhidevalue-dashboard

1. Initiate Virtual Environment

   python -m venv venv
   

   Activate Virtual Environment (for Windows Powershell)

   ./venv/Script/Activate.ps1
   

2. Install all dependencies on your virtual environment

   pip install -r requirement.txt
   

3. Create .env file by use the format like in .env.example

• Notebooks Trying and Playgroud of my data cleansing, managing and virtualizing before let it be .py file and run conditional automatically.
• Airflows Automate pipeline of data processing using DAGs with Apache Airflow
• Database MariaDB Database Configing with Docker Compose
• Superset Link to Git of Apache Superset Monitoring tool use it instead of PowerBI in future work.