September 6, 2019, by Aleisha Turner
Generating Insights from Big Data
The analysis of ‘Big Data’ is one of the main challenges faced today by both academia and industry. The project titled Value Enhancement for Data from Assets & Transactions (VEDAT), which was carried out in partnership with the ASAP group in the School of Computer Science aimed to “provide tools that enable intelligent, predictive modelling capabilities, including the integration and analysis of heterogeneous data types” in the heavy goods vehicle (HGV) sector. The project was completed in partnership with the company Microlise, which controls more than 30% of the HGV and van fleets across the UK.
The DRS enabled the generation of valuable insights and the development innovative advanced data analytics solutions, which are now being used by Microlise, their customers, and business partners to understand drivers, vehicle usage, safety procedures and service levels.
One key element of this project was combining previously unconnected, disparate data to create a platform that allows deriving high value benefits by both isolated data community members, as well as the whole disparate data owner community. Data exploration in this project resulted in novel techniques and tools tackling HGV transportation challenges in the context of Big Data, particularly what is often referred to as “Data Silo” blackholes. The developed solutions proved useful with a wide range of applications in other sectors with complex disparate data environments such as finance, engineering, biotechnology and informatics.