Getting to grips with Graph by Jenny, a mathematics undergraduate at University of Exeter

As a mathematics undergraduate student, I arrived at BiG Consultancy with relatively little knowledge or experience of working with big data or real-life data problems. However, during my time interning there over the summer, I was able to learn a great deal about the issues commonly faced everyday by businesses and institutions in the real world.

 Big Data is definitely a buzz word these days, and refers to particularly large volumes of data that simply cannot be processed in the same ways that smaller datasets historically have been. Organisations from almost every industry can encounter problems if they get inundated with data: in health care, patient records, treatments and response information needs to be organised efficiently so that it can be accessed quickly and accurately; in banking, a huge amount of data can stream in concerning risk, investments and regulations, as well as customer details; and in retail and manufacturing, businesses need to be able to access intelligence regarding the market and analyse their own company strategies effectively. On top of the large volume of the data, it can also be the sheer speed at which it can flow in at, as well as the variety, complexity and security of it, that causes issues.

To tackle these difficulties, new software, technologies and methods are being developed all the time, and companies are turning to specialists for help managing their data. At BiG Consultancy, I experienced first-hand some up-to-date challenges faced by real companies, as well as their route to a solution. In particular, I especially enjoyed learning about complex data visualisation, including how graph databases can be used to navigate multifaceted stores of information much more quickly, and easily, than conventional databases can be. Graph databases also allow for the exploration of data relationships to be investigated more thoroughly, and this visualisation of connections can really help to see how improvements in one area of a company, for example, can benefit another. As part of my work at BiG, I helped to classify entities for a dataset presented to us in preparation for input into a particular graph database, and was also involved with the early stages of learning how to query it. This was a brand-new area of analysis for me, but I felt I was able to really throw myself into it and utilise my mathematical skills already acquired through my university studies.

Working at BiG really opened my eyes into a field of industry that I hadn’t been able to truly get a feel for before. I am now inspired to use my developing data analysis skills on larger, more exciting projects in the future, and hopefully contribute to this fast-paced leading area of expertise that is sure to be instrumental for years to come.