The Database Generator is an automated solution designed to create and seed a database for my Database
project at the University of Porto. The commits are in https://github.com/RobertGleison/databases-training-projects/tree/main/shark-tank.
Please note that this is not a universal model, it only works with a specific CSV file. You can find the
dataset here.
In the context of this project, the primary objective is to generate a small UML model using a real dataset. The subsequent steps involve converting this model into a relational representation and creating and populating a database based on this dataset. While exploring datasets on Kaggle, I identified a comprehensive CSV file related to the TV show Shark Tank. Recognizing the challenges associated with manually populating a database with this data, I decided to develop a Java program to automate the entire process.
In this project, I used the following technologies:
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Spring: A comprehensive framework that provides support for various aspects of application development in Java.
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JPA (Java Persistence API): A standard Java specification for data access that simplifies the interaction between Java applications and relational databases.
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Hibernate: An object-relational mapping (ORM) framework that facilitates the mapping of Java objects to database tables.
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PostgreSQL: The final database file was generated in PostgreSQL, a Relational Database Management System.
