The project provides the analysis and evaluation of UK road accident data from 2005 to 2016. The objective is to examine the factors that affect the rate of accident, causality, and to investigate the likelihood of severity of the accident.
Following the data processing, we obtained a star schema data model with all dimensional Tables having one directional one to many relationships with the Casualty fact Table.
- Mid-aged drivers are more likely to be involved in accident.
- Most of the accidents occurred in the afternoon and evening periods. However, in the weekends most of the accidents occurred during Dusk (hours between 12 am and 3 am).
- Goods Vehicle Vans are more likely to result in a fatal accident than other vehicle types.
- The likelihood of accidents being fatal is almost four times in darkness (no lighting) condition.
- Most of the accident occurred around London.
- Accidents and casualties rate predicted to have a slight increase in the coming years.
- Road safety must be a high priority for policy makers, communities, and all road users.
- Improve road lighting conditions will reduce accident fatality.
- Educate all road users (including pedestrians).
Applied Data Science
I am a meticulous and value-driven Data Scientist with years of demonstrated expertise in data analysis, visualisation, and reporting, as well as in-depth mathematical modelling experience. Teesside University’s Masters of Applied Data Science degree offered appropriate and professional knowledge in data analytics through rigorous lectures, lab sessions, and assessment. Aside from learning about a variety of Data science approaches and technologies, I have also learnt about emerging ethical and security challenges in AI and Data Science in different sectors.
- Machine Learning
- Deep Learning
- Data Science
- Data Science Ethics
- Data Analysis
- Data Visualisation
- Data Analyst – Blue Atoms Media, Lagos, Nigeria
- Data Analyst Intern – Training and Research Dept. NIEPA. Ondo, Nigeria
- Office Assistant – Blue Atoms Media, Lagos, Nigeria
- Volunteer Vaccine Recorder – Primary Health Centre
- Volunteer Enumerator – Primary Health Centre ((NSHIP)), Ondo State, Nigeria