If you’re reading this then you’re probably thinking about (or maybe in the process of) applying to the Data School. What a great decision you have made. This may seem like a fairly long post, but I’ve tried to make it easy to navigate by breaking it into different stages of the application process. Hopefully, you’ll be able to jump to whichever section best matches the stage you’re at in the process.
I’ve been meaning to write this post for a very long time, pretty much since week one of DS. For whatever reason, it has taken me until now to sit down and actually get it done. In some ways, it seems rather fitting to pass on my knowledge of the process onto the future applicants just as I finish my training.
Please don’t feel that you have to follow every step in this blog. I’m just trying to provide some advice on what you can do to improve your chances. Don’t feel that if you don’t take all of these steps you won’t have a shot at success. This is just a guide and some tips from my own experience.
Before I get started, I thought best to share my application story, as it was probably an unusually long one. I first decided to apply to the Data School towards the end of April last year (scary how quickly the time has flown). I spent some weeks getting to know Tableau and working on my application viz before submitting my application applying for DS11 (starting in October). I applied so early because I was going travelling throughout the summer and wanted to try and have my place secured before I went. I got through the screening interview and then had a final interview in June. The outcome of this final interview was that I was to be re-interviewed in September, with the rest of the final interviews for DS11. There went my plan to have things secured before travelling. September came around and I was finally successful! However, I was starting in December in DS12 (far better cohort, all worked out well in the end).
Although there was a lot of time between initially applying and finally starting at the Data School, it gave me plenty of time to develop my skills ready to start and plenty of experience of the application process. This is why I wanted to share this blog, to give you the best possible chance of being successful and make the application process that little bit less stressful.
The application process is simple on the face of it. Find some data. Design a viz. Post it on Tableau Public and let us know. However, there are several other things I’d recommend to boost your chances.
Read all of the information provided, steps to applying can be found here
It may sound really obvious, but you’d be surprised how many emails we get asking questions that are clearly answered on the website. There is also a clear list of instructions on the email you will receive when you register to apply. We’re a very friendly bunch and always willing to help, but not being able to follow the simple instructions will make it seem you aren’t paying much attention.
We don’t look at CVs
This is one of the reasons the application process is so great, at this stage we aren’t interested in where you’ve come from or what grades you’ve got. We just want to see a willingness to learn and some competency at Tableau. Please don’t just send your CV in. Again, if you’ve read our website, this may sound obvious. However, we still get people sending in CVs rather than creating a viz! This won’t get you very far.
Attend one of our meet and greets
Our meet and greets are a great opportunity for you to come and get to know members of the Data School family. The evenings typically consist of an intro to The Information Lab and the Data School, followed by some demos of Tableau and Alteryx by current Data School students. The evenings are concluded with some relaxed networking with the Data Schoolers, whether they’re in training or on placement. There is also free food and drink at these events so if that’s not enough to entice you, I don’t know what is.
I can’t recommend attending one of these events highly enough. As well as being able to meet the team you can also get a feel for the company culture and whether this is really for you (I’m sure it will be). You’ll also pick up some invaluable tips for the application process (if this blog isn’t already enough!). Registration for our meet and greets can be found here.
Building your initial application viz
So you’ve attended the meet and greet, you’re ready to apply… where do you start?!
Take advantage of free learning resources
If you’ve never used Tableau before, do not worry, you are like many who have come before you. Start by downloading Tableau Public and following along with Tableau’s free online training videos. There are hundreds of videos on topics for the very beginner to the more advanced users. Take advantage of them no matter what your experience level! Another fantastic resource is the Data School Blog. Google anything to do with Tableau and 95% time you will find a Data School or The Information Lab blog on the topic. Use our knowledge, that is what it’s there for!
Find a data set you find interesting
Using data which you have a personal interest in will make building your viz far more exciting and enjoyable. There are all sorts of data sets out there, start by having a look on websites such as data.world, kaggle and Google dataset search. We get applications on a whole range of topics from sports to films to healthcare so show us whatever you like!
Find some inspiration
Go wild on the Tableau Public gallery. There are all sorts of amazing vizzes out there for you to gain inspiration from. Also, take a look at the blog posts from Andy Kriebel showing what it took to take into each DS cohort. This will give you a feel for the standard of viz required to get in! The standard is very high, however, try not to be intimidated. These vizzes take hours of work and several iterations to put together, they aren’t just thrown together in half an hour which brings me nicely onto my next point.
Take your time to build something you’re proud of
I cannot stress this enough. Successful applications have had lots of time and effort put into them, so make sure you do the same, it will be worth it in the long run! Submitting something you have rushed together in an hour just to save time will be unlikely to get you anywhere. Take time to go back over your viz and keep improving it until you feel it’s something great.
Seek feedback and iterate!
Part of the application process is seeing how well you respond to feedback. Iteration is a large part of life at the Data School and in the data viz world in general, so showing you’re capable of doing this will only improve your chances! Email us to say that you’re application is ready and you’d like some feedback, or alternatively call on people you might have met at a meet and greet! Everyone is more than happy to help you and want to see you succeed, that is part of the culture here. Drop someone a message on Twitter or LinkedIn and they will be more than happy to help you. Once you’ve made your changes, let the team know and they’ll review it!
Participate in community schemes such as Makeover Monday
There are many data viz community schemes out there such as Makeover Monday, Sports Viz Sunday, Project Health Viz. Between my two final interviews, I tried to participate in as many Makeover Mondays as possible and found it was really beneficial. Makeover Monday is a great one for people new to the data viz journey. It is run by Andy Kriebel and Eva Murray, each week they send out a data set and a visualisation which you have to re-design. This is followed up by a viz review where you can really learn a lot from other people’s work. This is by no means a requirement for the application process, but it will definitely help develop your Tableau skills through practice and your knowledge of data visualisation best practices will improve through viewing the work of others. It will also get you on Andy’s radar, which is never a bad thing when applying to a programme run by him.
So you’ve made it to the screen interview. As much as this is an interview, try not to work yourself up about it, as it is very relaxed. It won’t be like any other interview you’ve done. All you need to do is express your motivation and excitement about joining the Data School, which I’m sure won’t be difficult to do. The other part to this interview is giving a demo of your application viz. Explain the story of how you found the data set, the ideas you had when you initially started building. Talk about the iterations you took and how they improved your viz to the quality it is now. All we want to see is your thought process as to why you did something, whilst also being able to see that you are competent with Tableau. Be confident about your work! As long as you can justify why you made a particular decision everything will go swimmingly.
Final Interview Viz
In all honesty, this is the part of the application I found the most difficult. You’re provided with a pretty large data set, potentially the largest you’ve ever dealt with, and just told to make something out of it with no direction whatsoever. This can feel a bit overwhelming at first and you’ll come to learn that having this much freedom can have its pros and cons. It’s great because you can build whatever you feel like, however, sometimes you can feel a bit lost with no guidance.
Fully read Andy’s email
The email that Andy will send you will give you lots of little pointers on how to be successful at this final stage. This may again seem like an obvious point, but an invaluable one. You definitely don’t want to miss something that could boost your chances at that all important final interview.
Take some time to explore the data
Don’t just dive in and try to start creating your masterpiece. Take some time to explore the data, try to find some interesting trends that can start to build a story. It may seem like you’re going round in circles at times but this is all part of the journey to building a great visualisation.
Give yourself time away from the data
It can be easy to get bogged down in the data set and to spend all your available time on trying to create your viz. I was guilty of this at times and it can all get a bit much, you feel like you’re getting nowhere and you’re running out of time. Take a step away from it, go and do something to take your mind off things, whatever that may be whether that’s a run, going for a walk or just watching some TV. Taking that break will help clear your head and you’ll most likely come back with fresh ideas. I remember even having dreams about the data set and what I was visualising because I was so consumed by the data, so you’re not alone if you feel overwhelmed at times.
Seek feedback and iterate
Same advice as before with your application viz. Let us know when you think you’ve got something ready to go, and we’ll get someone to review it for you and give you feedback. Try to take the constructive feedback onboard, as it will likely be from a Data Schooler who has been through the very same process as you! Make sure you’ve left enough time before interview day for someone to give you the feedback and enough time for you to make the changes. I would advise trying to let us know a couple days before the interview day.
Your viz is ready to go and you’re getting ready for the final interview. On the day there will be two interviews with two panels, consisting of members of the core team here at The Information Lab.
Your first interview will be a 5 minute presentation on your application viz followed up with a couple of questions about your viz. They’ll largely be looking why you made particular choices and the processes you went through when building your visualisation. There may also be some loosely interview based questions as well.
The second interview is more of a proper interview, although nothing to be intimidated by. I’m sure at this point you will have realised that everyone is very friendly here and wants to see you do well. The questions here will about your motivations for joining the company and whether you’re the right fit for us. Take the opportunity to ask questions! It sounds cliche but this is as much about checking we’re the right fit for you as us checking you’re okay for us.
A few pointers:
- Take time to practice your presentation, it will show in the interview if you haven’t rehearsed. This is usually the part people are most nervous about, so if this goes well and you’re feeling confident, the rest of the interview will be a breeze.
- Have a thorough look at the Data School website and The Information Lab website. Watch the videos on how the Data School was formed and the history behind it.
- Ask questions! We want to see that you’re interested in the company. Sometimes it can seem difficult as we provide you with so much information about the scheme in the application process but try your best to come up with these before the day!
- Relax and be yourself! We’re not an intimidating bunch and everyone is very easy to get along with. Get here early and just relax into the interview by chatting to current Data Schoolers, they’re always floating about and will want to get to know you. Just strike up a conversation and the interviews will feel much more relaxing.
- Enjoy it!
If you’re not successful after the final interview, try not to get too disheartened about it. It may seem like a bit of a kick in the teeth after all the work you’ve put in. Many current Data Schoolers got into the programme at the second time of asking, I had two final interviews, it’s definitely not unheard of.
Once you’ve digested everything, if you want to take another crack at it. Keep practising, work on your skills, participate in community projects like Makeover Monday and try again. It isn’t frowned upon at all to re-apply, if anything it shows determination and that you really want to be here. We don’t have a process of waiting for a period of time before you apply again so just have another go if you feel like this is the place you really want to be!
All I can say at this point is good luck! Hopefully you’ve found my pointers helpful and feel free to reach out to me if you are applying and want some advice. You can get to me on twitter here.
Most likely my last blog post so goodbye Data School blog, its been a blast!