This repository contains some of the database projects I completed while taking the course Principles of Database Systems during the Fall 2019 Semester at Metropolitan State University of Denver.
This project builds a relational database in SQL from this dataset. A python script is used to parse the data from its original format and to enter the data into an SQL database.
This project loads a provided database into SQL from a file. The dataset and overall database structure is similar to that of the Dataset Parsing: SQL project outlined above this one. This project demonstrates the use of various types of SQL queries to find specified subsets of data.
This homework includes examples of MongoDB queries that would be used with the included data set (companies.json)
This project loads a dataset (found here) of genetically connected diseases into Neo4j and demonstrates how data can be exported, parsed, grouped, and labelled in order to visualize data and create hypotheses. A Python script is used to create a parse, group, and label data and output a cypher that can be used to enter the grouped communities into Neo4j. For this project, a text file with a hypothesis about one of the communities (selected by the student) was required as a deliverable. I have included my hypothesis to show how Neo4j community data can be applied.