Read how Gareth, MSc award in maths winner from Exeter University, applied his knowledge at BiG

This summer I got the chance to work with BiG Consultancy whilst finishing my Masters course in Computational Finance at Exeter University. I was interning at Crowdcube, an equity crowd-funding platform, who use BiG team as their Data experts. I first met the team at BiG in my third week. I ended up enjoying it down there so much that I worked from their office for the remainder of my internship!

My task was to help implement a data driven process to find companies suitable for crowd funding.

BiG were on the track to achieve this through machine learning, with a data set that was deep and rich enough to facilitate this. Although, in order to deploy the more in my view glamorous machine learning algorithms to achieve speed efficiencies, there was a necessary grunt work involved of building our own clean and complete dataset. I was shown how to call APIs in Java, a programming language I had never used before, and write the results to a database.

The project began with warehousing the data in Amazon Redshift. However, due to the large volumes of data we were collecting we progressed over to a cloud based system, Cassandra – now that’s Big Data! Random Forest was the algorithm of choice – a decision tree based algorithm. A training set of pre-classified companies was used to train the model, with various rules being applied to evaluate the larger dataset. By the time I had finished my internship, we had created an environment capable of producing hundreds of leads a week, with the model becoming more and more intelligent as feedback of the lead quality was fed back in.

My time at BiG definitely complemented my academic work where I was focusing on applying Monte Carlo methods to price path-dependent options. This is a process where the price of an asset is simulated thousands of times to obtain the average price of the option – a technique which is useful when there is no analytical solution available.

Both projects had a heavy emphasis on data and programming with methods and theories applied feeding into each other. For example, I found the role of random number generators very interesting. In particular, how they could be replaced with low-discrepancy sequences in order to reduce variance, whilst still keeping the “random” properties needed for the Monte Carlo method to work. This meant that the option price would converge to the correct solution quicker than the standard approach.

Even simple rules of programming that I was taught at BiG such as how to structure code and export results to a database helped me when it came to writing up my report and visualising the results.

Big Data is an extremely fascinating topic and I would advise anyone with a passion for numbers to read into it. Thanks to the team at BiG for teaching me so much, it was great having the chance to work with you!

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.

Learning Java with Monsters

At BiG we’re passionate about innovating with data but it’s coming together of brilliant minds that makes what we do possible. Rich flow of fresh talent and attitudes is crucial to keep our enthusiasm for problem solving with data infectious.

Here is what our intern, 4th year Mathematics student Conor, made of working at BiG. His responsibilities included: writing code, analysing data and learning to operate office robots (a form of machine learning!)

My name is Conor and I’m a 4th year Mathematics student at the University of Exeter. In June I spent one month as an Intern for BiG Consultancy. Before my internship, I had limited experience with programming and knew very little about big data. Once I had arrived, met the team and had a tour of the office, I was given my first task. I was to spend my first two weeks learning how to use and program in Java. I had no prior experience with Java, so it was a steep learning curve, but Gerry helped me to overcome any obstacles that I faced. I was challenged to create a text-based game by the end of the two weeks where the hero, Conor, had to go through different rooms, encountering and defeating monsters along the way. I was proud to have created this game from scratch after such a short space of time. It really opened up my eyes to the many applications of Java.

After successfully playing Frankenstein and creating an army of monsters, I moved from learning about the software development aspect of BiG Consultancy to data visualisation. In the next two weeks, I learnt how to use SQL to extract data. I found this to be significantly easier to work with than Java! With the help of Chris, once I had created data tables, I was able to manipulate them to create visual representations using programs such as Tableau and KNIME. This made the data easier for a client to analyse.

I really appreciated the time that I spent working at BiG Consultancy. With the help and guidance of the team I was able to develop my skills in programming in Java, as well learning about data analysis and visualisation. In addition, this was the first time that I have worked in an office environment, so this was also a very good experience. I especially enjoyed the coffee machine! Throughout the month internship, I learnt a lot about the rapidly developing world of big data and am excited to use the skills that I acquired here at BiG in my future endeavours.

#DataMunch – Tom More, IP & IT law specialist at Stephens Scown on ‘What will change with GDPR?’

Tom advises start-ups and multi-national businesses alike on legal issues within Technology and Data sector as well as having in-depth experience in IP. He is valued by IT clients for his intrinsic understanding of both the law and its practical application.

Here Tom gives an entertaining report on the dwindling light of the Data Protection Act and many unknowns of the new General Data Protection Regulation. What does the looming compliance deadline mean for businesses and what should you do to prepare for it?