I know how hard it is to go through the application process for Data School. It seems long and resource-intense but believe me when I say, it is more than within your reach! As someone who went through the process quite recently, I thought I’d share a couple of personal tips which hopefully will help you in your application. Good luck!
- Tableau is scarier than it looks!
When I first downloaded Tableau, I thought I’d never be able to build anything even remotely good enough to submit in my application. It’s an extensive tool which can very quickly overwhelm you with all the functionalities it provides. But trust me - it really isn’t as hard as it might seem. Just like any other data viz programs, Tableau’s design to be intuitive and assist you with whatever you’re trying to show. It sometimes takes a while to get used to its functionalities but with all the support online (including Data School resources, hundreds of blogs and never-ending Youtube tutorials) you can very quickly get around the basics, which are more than enough to get you into DS. All you need to do is give it time!
If you ever feel like it’s too much, remember - a lot of people who joined DS never heard of Tableau before they joined! One of the things that’s being assessed on your application is whether you’re ready and willing to learn and building a dashboard is the best evidence of that!
- Show that you can analyse, no one expects (or wants!) you to be a Viz expert
Drawing on the above, DS coaches aren’t looking for experts. The whole point of the course is to find people from diverse backgrounds who often have never worked in data and teach them what it is about and how to use the analytical tools. What everyone hopes to see in you is that you can go through the data and analyse it. Show that you can work with the dataset by pulling out some insights, findings or trends. Overcomplicated charts are definitely not required!
- Tell a story!
Best application dashboards aren’t supposed to show off how many different charts you can make, talking about multiple things at once. Instead, try showing your analytical skills by looking into telling a story with your data. For example, in my final application dashboard I had to work with a dataset containing incident information for London Fire Brigade. One approach to this viz could be to just give an overview of the fires in London, where they happened, how they changed over time and how much they cost the LFB. It’s a valid approach to this task but also a one that most candidates will think of. This is why, instead I looked into telling a story, focusing only on the false alarms and how those reflected on the overall volume of incidents in London. By providing an insight into only one type of incidents I was able to show a different perspective simultaneously showcasing that I am capable of identifying a trend within a large data set!
You can see my final application viz here. Remember that although it helped me to get in, it’s far from perfect so don’t take anything you see there (or anywhere else) as a definite template! Treat other vizes as an inspiration!
- Use the feedback and make sure to implement it
DS coaches want you to improve. When you apply they will give you feedback on what you can make better in your initial application. USE THAT FEEDBACK AS MUCH AS YOU CAN! What everyone wants to see is that you’re ready to learn more and improve from your previous work. Implementing their advice will show that you are listening and that you’re involved on top of increasing the quality of your viz!
- Reach out to whoever you can
Starting a journey with Tableau (or data analysis in general) can be very isolating, especially if you’re doing it alone. I know it can be hard, especially if you don’t have any expertise to rely on. This is why, if you’re really serious about DS, you should consider finding people you can talk to and ask them for help with your application! The best way to do that is to come to one of the Meet & Greet events (organised every other month) where you can speak to people currently training or working in Data School. We all went through the same process so everyone understands how hard it is to do it on your own. Don’t hesitate to ask for help, anyone who has some spare time would be more than happy to give you some advice (I mean it!).
If you can’t come to the Meet&Greet, you can try reaching out to any of us online - try Linkedin or Twitter. It doesn’t hurt and it may easily boost your chances of getting in. Worst case scenario, whoever you’re messaging will say they are too busy, but I assure you there will always be someone happy to spare a couple minutes to talk you through the process.
- Use the online resources
Believe it or not but Tableau has a huge community present all over the world with many self-taught experts all over the world. DS blog, youtube, Tableau Public and online forums are only a couple of knowledge hubs which can provide you with all the expertise you might need. Browse through them and you can very quickly overcome the hurdles of starting with Tableau!
- it is NOT 'too good to be true'
Almost of my cohort said the same thing on our first day - “this program is too good to be true, there is no way there isn’t a catch”. And I know this might not seem too convincing (I am posting on DS blog after all :) ) but trust me when I say - there really isn’t a catch. DS is a 2.5 year program which literally invests in you to empower you as a data consultant. You’re getting paid for it since day one and by joining you enter one of the friendliest work environments you can find (trust me, I know - I’ve dabbled in the corporate world before joining). This is not one of those places that tells you ‘we are your family’ or offers ‘flexible hours’ just so they can make you stay till 9pm on a Friday. The philosophy of DS is to create the best environment for learning, allow you to ‘network’ with like-minded people and excel as a data specialist (which in turn has a positive spillover effect on the company). Everyone is very transparent about what we do here and this transparency makes it very clear that there is no ulterior motive or hidden catch. If you like data and want to work with it, DS is definitely a place for you :)