Development of a data platform for bicycle lane transits

With the growing demands of sustainable urban transportation methods, this thesis presents the development of a data platform that is capable of tracking and managing urban bike traffic. A data platform dedicated to count bike lanes transits can be helpful for informed decisions and to encourage further growth of cycling as the main option for transportation in urban cities. Data engineering plays a pivotal role in this context. A well-designed data pipeline has been implemented for data validation, cleansing and transformation steps in order to improve the quality and reliability of data as it is constantly and automatically generated. The project has been executed for a public sector client focused on environmental and urban mobility goals. The three-tiered proposed solution entails the following phases: firstly, developing a script, through REST API calls, which automated the pulling of data and standardized format and structure across sources. Then, the development of a data warehouse is pursued through an ETL pipeline, where data is integrated and transformed to a central repository in preparation for analysis. And finally, developing a custom visualization of the data on a dashboard where authorized users can view trends and gain interesting insights. Results have been objectively evaluated through fixed KPIs following accessibility guidelines necessary for the open source publication.