First ‘big data’ research approach to graduate earnings reveals significant variations depending on student background, degree subject and university attended.
Data from location-based social networks may be able to predict when a neighbourhood will go through the process of gentrification, by identifying areas with high social diversity and high deprivation.
Desislava Hristova (Computer Laboratory) discusses how data from location-based social networks can be used to predict when a neighbourhood will go through the process of gentrification.
Visual data will revolutionise the way companies talk to their customers, according to researchers at the Cambridge Judge Business School.
Analysing graduate earnings using anonymous administrative data can show how earnings vary for graduates and indicate which skills are in short supply, says Cambridge education professor Anna Vignoles.
Big data has captured the world’s attention, with talk of a new Industrial Revolution based on information, and of data being one of the 21st century’s most valuable commodities. Today, we commence a month-long focus on research that uses, produces and interrogates huge datasets.
Cambridge computer scientists have established a new gold standard for open research, in order to make scientific results more robust and reliable.