Where I started
This time two years ago I didn’t realise the job I am doing now existed. I had just had my first contact with Tableau a few months earlier, through my job at Leicestershire County Council. Diligent applicant that I was, I had researched the two people who would interview me on LinkedIn before the interview. One of them was Rob Radburn, who highlighted on his profile that he was a Tableau Zen Master. I decided to download a trial version to get an idea of what that entailed and spent about half an hour with it, fairly helpless, but could at least show at the interview that I had done my research. I got the job, and relocated from Norwich to Leicester a week later.
At LCC I mostly spent my days doing qualitative analyses and creating surveys for other council departments. While I was working on topics I found important, it was also at times frustrating. For instance, when I was asked to derive insights that should shape council policy from a survey that had seven respondents. Or when I analysed opinions on a new policy, even though it was already signed off and going ahead, no matter what the public thought. I was on a temporary contract, hired through an agency, and after six months I was invited to apply for the permanent role that had become available. I realised I did not have a great desire to stay in Leicester and wanted to move back to London. I also felt that I wanted to build my skills quickly and wasn’t sure I would be able to achieve that in this role.
I have a BSc in Psychology and a MSc in Social and Cultural Psychology and I learned things in these degrees that have shaped my personality, the way I see the world and the way I do my work. I was fortunate enough to have a job at the council that was relevant to my studies, something that isn’t a given for recent graduates. I applied my knowledge of survey design to create consultations, performed basic statistics on results (like deciding you can’t draw conclusions from a sample size of seven) and wrote literature reviews for other departments on a variety of topics. Unfortunately, university often doesn’t equip you with very practical skills, which would be useful when you start a job like this, and had taught me a lot of theoretical and broad concepts, while not making me an expert at anything. I felt like I was held back by my limited knowledge of Excel and Tableau. I didn’t feel like I had an edge when applying for jobs, nothing that made me stand out amongst all the other graduates with limited work experience and I wasn’t sure how I was going to be able to get this edge, and considered taking out some time for additional training before moving back to London.
So when, after I told my supervisors that I was leaving, Rob took me aside and told me about The Data School, I got pretty excited. I could practice Tableau on my own when I had nothing else to do and had started to work on small Tableau tasks for printed reports. I noticed quickly that the days when I got to spend my time learning Tableau were my favourite, and I loved the thought that I would get much more time to do this.
What I expected
The Data School was a unique opportunity to be paid to learn something that I already knew I enjoyed. It promised to equip me with the practical skills of becoming an expert in specific tools, which would allow me to effectively apply the knowledge I had gained at university.
While the selection of placement companies didn’t excite me – most of them being large, private organisations – I also knew how valuable this work experience would be and that it would help me to reach my career goals in the long term. Having to adapt to novel environments pushes you out of your comfort zone, and you can learn a lot when doing that. The ideal role will continue to develop you, no matter how long you have had it, and you are lucky if you manage to find such a role; but it is a special set of skills that get refined each time you start a new job. I did this five times in two years: Once when starting at The Information Lab and then again for each of my four placements. I expected this to be challenging but, as with all things challenging, enriching.
What I didn’t expect
When applying for the Data School, Alteryx was just one of the things that came with the curriculum. I had no understanding of what it was and accepted it as something I would get through to be able to become a Tableau expert. I didn’t expect to develop the same level of passion for it as I had for Tableau. What I love now about Alteryx is that you have defined problems, with defined solutions. Tableau dashboarding is to an extent subjective; there are many ways you can answer the same question. In Alteryx there are many ways to get to the same solution, but there is only one answer you need to arrive at, and once you have you can lean back with the satisfaction of having completed the problem. Alteryx, much more so than Tableau, gave me an understanding of the wider field of data and it allows me to do things I never thought I could, and that I believed were only attainable for expert coders and those with a background in computer sciences.
These were my expectations, but what was it actually like going through The Data School? I’ve written a second post to share my experiences of the four months training and my four industry placements.
Naledi + Data 