Welcome to the Neo4J Airport Data Analysis Project! This repository contains the work of our team dedicated to exploring and analyzing airport data using the Neo4J database. Our aim is to uncover hidden patterns and insights from the dataset through complex queries and visualizations.
This project involves the use of Neo4J, a graph database, to analyze and visualize data related to airports and their routes. By querying the database, we aim to uncover interesting patterns and relationships within the data. The project includes a comprehensive report detailing our methods, queries, and findings, as well as the datasets and query files used for this analysis.
- Description: This file is a comprehensive report that outlines the entire project. It includes an explanation of our methodology, a description of the datasets, the queries we used, and the results obtained from these queries.
- Description: This CSV file contains the node list for our Neo4J database. It includes detailed descriptions of each airport node in our dataset.
- Description: This CSV file provides the edge data for our Neo4J database. It includes information about the routes between airports, with 'from' and 'to' edge data.
- Description: This text file contains all the queries we used to unveil hidden patterns in the airport data. These queries are a key part of our analysis process.
- Description: This file includes the query used to load the dataset into the Neo4J environment. It also contains some basic visualization queries to ensure that the data connections are working correctly.
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Mohammad Jawad Ahmad: As the primary author of the comprehensive report, he combined and organized all the group work. He was instrumental in setting up the GitHub repository, ensuring all components of the project were well-documented and accessible.
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Mariam Hussein: Mariam was responsible for downloading and setting up the Neo4J database. She practiced all the queries on her laptop, playing a role in troubleshooting and resolving any errors encountered during the project’s development.
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Fatima Chalhoub: Fatima spearheaded the task of finding the perfect dataset for our project. She crawled the web, inspecting several datasets before narrowing down the choice. Her dataset selection were pivotal for the foundation of our analysis.
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Mohammad Jawad Zeinniddine: Mohammad was the brains behind the unveiling queries. He conceptualized and executed the queries that unearthed the hidden patterns in our data. His thinking drove the analysis of the project.
It's important to note that while each team member had specific roles, the success of this project was a group effort. All team members contributed to working out the queries, brainstorming ideas, and refining our approaches to ensure the best possible outcomes in our analysis.
This project utilizes the Neo4J database for storing and querying data. For more information on Neo4J and its capabilities, please visit Neo4J's official website.