This project focuses on designing and implementing a complete data warehouse system to analyse punctuality across UK airports. Using 24 months of aviation punctuality data, I developed a star schema, performed ETL processing, built fact and dimension tables in Oracle SQL, and produced visual analytics in Tableau. The goal was to uncover trends in delays, cancellations, and airline performance through clean, structured data workflows.
2025
Data Engineer
Data Analyst
Data Warehouse Design
Data Visualisation
The aim of this project was to transform raw UK airport punctuality datasets into a clean and structured analytical system. Starting with 24 CSV files, I implemented a full ETL process by extracting raw data, cleaning inconsistencies, removing duplicates, standardising formats, and aggregating key metrics such as delays, cancellations, and early/on-time performance.
I designed a data warehouse star schema consisting of five dimension tables (Time, Airline, Airport, Area, Service Ratings) and one central fact table capturing monthly airport punctuality metrics. Oracle SQL was used to build and populate the warehouse, enforcing data integrity through primary and foreign key constraints.
With the warehouse complete, I created four Tableau visualisations exploring airport and airline performance, quarterly trends, geographical distribution of poor ratings, and the relationship between delays and cancellations. These dashboards reveal insights into UK aviation operations across 2023 and 2024.
This project focuses on designing and implementing a complete data warehouse system to analyse punctuality across UK airports. Using 24 months of aviation punctuality data, I developed a star schema, performed ETL processing, built fact and dimension tables in Oracle SQL, and produced visual analytics in Tableau. The goal was to uncover trends in delays, cancellations, and airline performance through clean, structured data workflows.
2025
Data Engineer
Data Analyst
Data Warehouse Design
Data Visualisation
The aim of this project was to transform raw UK airport punctuality datasets into a clean and structured analytical system. Starting with 24 CSV files, I implemented a full ETL process by extracting raw data, cleaning inconsistencies, removing duplicates, standardising formats, and aggregating key metrics such as delays, cancellations, and early/on-time performance.
I designed a data warehouse star schema consisting of five dimension tables (Time, Airline, Airport, Area, Service Ratings) and one central fact table capturing monthly airport punctuality metrics. Oracle SQL was used to build and populate the warehouse, enforcing data integrity through primary and foreign key constraints.
With the warehouse complete, I created four Tableau visualisations exploring airport and airline performance, quarterly trends, geographical distribution of poor ratings, and the relationship between delays and cancellations. These dashboards reveal insights into UK aviation operations across 2023 and 2024.
This project focuses on designing and implementing a complete data warehouse system to analyse punctuality across UK airports. Using 24 months of aviation punctuality data, I developed a star schema, performed ETL processing, built fact and dimension tables in Oracle SQL, and produced visual analytics in Tableau. The goal was to uncover trends in delays, cancellations, and airline performance through clean, structured data workflows.
2025
Data Engineer
Data Analyst
Data Warehouse Design
Data Visualisation
The aim of this project was to transform raw UK airport punctuality datasets into a clean and structured analytical system. Starting with 24 CSV files, I implemented a full ETL process by extracting raw data, cleaning inconsistencies, removing duplicates, standardising formats, and aggregating key metrics such as delays, cancellations, and early/on-time performance.
I designed a data warehouse star schema consisting of five dimension tables (Time, Airline, Airport, Area, Service Ratings) and one central fact table capturing monthly airport punctuality metrics. Oracle SQL was used to build and populate the warehouse, enforcing data integrity through primary and foreign key constraints.
With the warehouse complete, I created four Tableau visualisations exploring airport and airline performance, quarterly trends, geographical distribution of poor ratings, and the relationship between delays and cancellations. These dashboards reveal insights into UK aviation operations across 2023 and 2024.