This project showcases the implementation of a data engineering solution using Python within a Jupyter Notebook environment. The primary objective is to establish a connection with a PostgreSQL database, create three tables (account_detail
, personal_detail
, and location_details
), and define a relational model between these tables, including the establishment of relationships. The project also utilizes the Pandas library to read data from CSV files into DataFrames for further processing.
- Notebook File: The core of the project is contained within the Jupyter Notebook file named
data_engineering.ipynb
. - Data Files: The necessary CSV files (
account_data.csv
,personal_data.csv
, andlocation_data.csv
) are provided in the project directory. - README: This README file provides an overview of the project, its objectives, and instructions for replicating the setup and running the notebook.
Before running the notebook, ensure you have the following dependencies installed:
- Python (version X.X.X)
- Jupyter Notebook
- Pandas
- psycopg2 (for PostgreSQL connection)