Gareth Hampson, a data scientist who graduated with an MSc in databases and web-based systems from Salford University, recently won a SAS prize for his excellent project using SAS® Enterprise Miner™. He has also been profoundly deaf since the age of 4 due to meningitis.
We spoke to Gareth to find out more about what he does, his course, his projects, his hobbies and future plans, and why he uses SAS.
- Where did you grow up and how did you first develop an interest in analytics?
I grew up in Stockport, a town south of Manchester. I have always had a very logical and analytical mind, but I didn’t know I was interested in analytics until I did the Salford MSc course.
- What made you choose the Salford MSc degree course?
I was working for Stockport Council as a Management Information Officer. An MI Officer is an analyst who deals with data and reporting inquiries across all areas of the organization, as well as from central government and the general public.
Additionally, I was initiating projects to streamline workflow and processes within the HR department, often based on Microsoft Access and SQL Server, and I also developed the HR intranet site for the council. This was an area of work that I especially enjoyed.
After a reorganization within the council, I decided to formalize my knowledge by embarking on a higher degree. I wanted to be involved with databases, and also to develop web-based applications hosted in the cloud. The Salford MSc in databases and web-based systems jumped out as covering all my aspirations.
- Has your disability held you back in your career choices?
Inevitably, yes. Any role that requires significant verbal communication will be difficult. My original career path was as an opto-electronic engineer for Hewlett Packard, after completing my BEng in electrical and electronic engineering at Loughborough University. My thought process for this career path was to be in a professional role that might not necessarily require significant communication. My father was also an engineer, so this gave me a background in engineering.
Over time, I discovered I was more interested in IT, rather than engineering. IT is another good career for deaf people, especially in development. There are still areas that might be difficult, e.g., in heavily client-facing consultancy roles.
- What did you like best about your course?
Being able to go in depth into the complexities of database systems, and learning how to perform data mining using SAS Enterprise Miner. The web-development module was also another highlight.
Special mention must be made of the course leader (and my dissertation supervisor), Dr. Mo Saraee, who has a hugely infectious and humorous way of lecturing and project supervision.
- What did you find the most challenging on your course?
Probably forcing myself to take some time off every now and then! I was very focused on the course.
- Greater Manchester Police
I performed data mining using the CRISP-DM framework and SAS Enterprise Miner to explore the potential of data mining on police crime records, with a view to finding patterns within the data to assist in crime reduction and prevention. As an example, an interesting pattern was found relating to the age of the offender, the type of crime and certain offender home address outcodes within Manchester.
- Greater Manchester Fire and Rescue Service
Below is the abstract from Gareth’s dissertation:
This project gathered incident records from the Greater Manchester Fire and Rescue Service (GMFRS), with the aim of demonstrating to the Service the viability of incorporating Data Mining techniques into any future risk modelling and resource allocation analysis that GMFRS may perform.
Focusing on three specific incident categories; Secondary Fires, Primary Fires and Special Services over the period 2009 to 2014, this study tested several different types of predictive modelling algorithms using the SAS Enterprise Miner data mining suite.
By examining the results generated for each category, this study demonstrates the potential of such techniques to reveal hidden patterns within the data, that are worthy of further analysis and contextual study. The results presented during the case studies are only a small example of the potential inherent in using data mining techniques on fire and rescue incident records.
Such knowledge is particularly useful for improving resource management for GMFRS (e.g. in identifying areas for preventive intervention), and also in enhancing risk modelling analysis. This study concludes by proposing future areas of research to ensure that GMFRS and indeed, other Fire and Rescue Services within the UK, gain the maximum benefit from data mining.
- What do you like about using SAS for analytics?
The SAS suite is probably the de facto professional analytics software used in industry, and having exposure to it at university via SAS OnDemand for Academics is a significant advantage in the job market.
Also, a lot of the SAS-produced user guides and white papers were a major reason for the in-depth understanding I developed around data mining, in addition to the university lectures and tutorials.
- What are your future plans, and will SAS be a part of them?
As a result of completing my MSc, I realize that my interests lie within data engineering in the big data field, i.e., in the development of Hadoop and other large-scale distributed data systems. I would certainly hope to be using SAS in order to analyze the data.
In any case, I intend to be doing some form of business intelligence and data development role, potentially with a view to developing web-application systems to analyze and visualise data, e.g., by using the SAS API.
I am looking for the entry role that will enable me to gain a foothold into the industry. I’m sure I can develop and progress rapidly within the company that gives me this opening.
I enjoy the outdoors and outdoor activities of all forms. Now that summer is here, and I have a bit more time since the MSc finished, I intend to spend more time climbing in the Peak District, an activity that I have neglected for a long while!