Blog: Big Data is not just for big companies!

Date: October 4, 2017

By Polly Halton, BI Analyst

I never really thought about my career growing up. I was good with numbers, so I did Maths at A-Level and I did well, so I thought ‘you know what, I’ll do that at University too’ and I revelled in every minute of it! Long surpassing arithmetic, numbers were essentially out the door, I was now learning the real language of maths.

My days started to fill with Greek symbols, computer science and furious scribbling in notebooks; I felt in my element. Soon though, the 3 years were drawing to a close, I had to start thinking about what I wanted to do out there in the ‘real world’. What do people with maths degrees do? I knew I wanted to use my knowledge, I didn’t want to be a maths teacher, so what else was there?!

I’m happy to say that teaching isn’t the only option for a budding Mathlete. Just over 3 years on from graduation, I have found myself at Catax, as a Business Intelligence Analyst. I feel lucky, as unlike a lot of companies their size, they have seen the importance of companywide business analysis and are keen to be involved in the ‘Big Data’ movement. Despite being at the company for just two years (starting off in the Marketing Department), I have just finished my first quarter in the brand new dedicated Business Intelligence Department.

As an extrovert with an analytical view on the world, it suits me down to a T! I’m not tucked away in the basement, but sitting on the top floor of the office, in a room full of big bright windows and a beautiful view of Goose Green, here in Altrincham.

To kick off our ‘average’ week, we have a team meeting where I feel like John Nash in a Beautiful Mind, using a potentially excessive amount of white boards to outline our goals; what we are aiming to achieve, and the road map for how to get there.

In essence, my role is to ask questions, whether it is questioning the Data, Managers, or the Staff; my aim is to get the unbiased answers. It would be incorrect to say I don’t spend a lot of time crunching data in spreadsheets, linking data sources and searching for causality but the job is a lot more social than that. As part of my role, it is essential that the we understand the current processes across the company, how the data related to these processes is recorded as well as, using data to consult on any changes. This means spending time with other departments and generally being curious about how they do what they do. Contrary to many people’s beliefs, my 9-5 is spent on my feet and away from my desk gathering information and understanding what is going on.

Our dedicated Business Intelligence Department is still in its infancy, Catax has historically focussed on the ‘what’, rather than the ‘why’. This has allowed for more flexibility within the role and the department ensuring we are working in the most efficient manner. The role doesn’t stop there; my upcoming months are packed full of training sessions and conferences. Recently, I joined the Manchester BI User Group where not only am I learning a lot, but also get to eat pizza, drink beer and admire the beautiful views of the city centre. We are encouraged to learn and absorb knowledge and speak with people in the analytics industry to find out what they are doing, to swap ideas and uncover innovative notions that can be implemented within our department, allowing us to have slick and effective Business Intelligence team from the outset.

Overall data science may be new to Catax but we are already reaping the rewards and it is fast becoming an additional factor that sets us apart from the competition. The data allows us to take a step back and look at the company as a whole, giving us the opportunity to truly comprehend how each department is intrinsically linked, to be able to drill down and find those nuances in processes and to offer solutions that increase efficiency.

We are no longer relying solely on gut feeling, but using evidence alongside experience allowing for greater confidence in decisions. The days of mistaking ‘correlation for causality’ and claiming, ‘theory in confidences’ are long gone.


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