It’s the final week of training for Data School 11 with our first week of our six month placements starting next Monday. Unlike the training I’ve been provided in other jobs the past 4 months in DS have been comprehensive, extremely useful and enjoyable. It is the only job I’ve had in which I’ve actually looked forward to going into work (other than Deliveroo which was just riding a bike around during summer). In this blog I’ll discuss how I got into DS, the general DS training structure and some thoughts for the future.

Getting Into DS
I applied for the Data School after hearing about it on the SuperDataScience podcast. The training was mentioned a lot and sounded too good to be true. Paid to be trained to a high level by industry experts with consistent real world projects throughout (it turned out to be true). The application requires you to submit a viz made in Tableau, something I’d recently discovered on an online data science course (also from SuperDataScience).

I painstakingly compiled together an excel sheet of Premier League results tables along with any other relevant information I could find. I then created a series of dashboards looking into various questions and linked these together with a single connecting dashboard.

I was initially given feedback on the viz from Carl (one of the DS coaches) and iterated before submitting the final application. I passed the first stage and arranged a phone call/interview to discuss the viz with Andy. The call was a relatively informal skype chat in which I explained various parts of the viz and talked about why I was interested in data.

I was planning to go travelling for a few months after that so my application was put on hold until I returned but Andy encouraged me to get involved in the Makeover Monday community project. The project encourages people to redesign or improve a viz and post it online for feedback. I took the advice and it helped to improve my skills massively.

Returning from travelling I continued to join in on the Makeover Mondays and was given a dataset to make a viz for the final interview. I wasn’t accepted based on the first interview/viz but was encouraged to keep working on my skills for a second chance closer to the application deadline. Thankfully I got in the second time round and I think practising with Makeover Monday datasets was a key factor for this. I also planned out how I wanted my viz to look and the story I would go through before diving into creating it the second time round, something I also felt helped.

Structure of the DS
I was unsure what to expect with my first day in the DS but again it turned out to be great. It started off with introductions to the company and getting downloading software etc. We were all given laptops and bags which we get to keep for the duration of the Data School.

In our first week we were introduced to the power of Alteryx. I spent ages copy and pasting to excel and using vlookups to get the data how I wanted for my application. After a day with Alteryx this was a task I could do in less than an hour. We were also given a project in our first week to redo our application viz using Alteryx to add more data.

The first half of the training up to Christmas then flipped between Alteryx focus and Tableau focus covering all the required topics. There was a wide range of topics covered such as spatial analysis and predictive analytics in Alteryx, but with more of a focus on data prep. We also did stats in Tableau, as well as server, best practices and all the features and techniques such as blending, table calculations, level of detail calculations etc.

After Christmas we consolidated our learning from the first two months, going over topics we felt weaker on or just wanted a refresher on. This was great for confidence as it allowed us to reflect on how much we’d learnt in such a short amount of time.

We also had a project every week during the training to either help consolidate something we’d learned that week (macro’s, postgres etc.) or for a client using real world data. Both projects types were great but the client projects were particularly valuable. They gave us insight into real world data problems and a chance to work with the kind of messy data sets that are the norm in most businesses. The consistent projects were also a great way to improve presentation skills as we had to present what we made every Friday.

We also developed many other skills as part of the training such as consulting, agile project management and teaching. For example as part of the training we had to teach something we’d learned to members of the public.

Thoughts For the Future
Now that my training is finished I’m looking forward to starting my placement and applying all the skills I’ve learned. I also hope to keep learning and developing my skills which is something I’m sure being a part of the Information Lab community will help. To anyone thinking of joining the DS I recommend it highly, the training’s been great!