If you are like me and are interested in transitioning into a career in data analytics but don’t have any experience or technical skills in the area, do not fret! Here are some of my top tips that I personally found helpful in getting that first interview and subsequently receiving the job offer from the Data School Down Under.

 

Familiarise yourself with Tableau

 

Tableau is the software you will need to be comfortable with for the application process. You are required to find a data set, and then use Tableau to create a visualisation on that data. If successful in the first interview, the Data School will give you a data set to create another dashboard on for the final interview. So being comfortable with Tableau is a must!

It is easy to jump in to Tableau and start creating some cool looking charts intuitively without truly knowing what is going on. I strongly recommend taking the time to understand the basic levels behind Tableau functions first. You may be asked to explain the methods used to achieve a chart, or what the chart is showing in the interviews. Therefore it is really important to build a foundation with the basics of Tableau and be familiar with the software user interface.

I personally found the learning modules on the Tableau Public website a great place to start, being someone who had never even heard of Tableau before! YouTube also has a plethora of instructional videos that provide step-by-step instructions to help create charts or understand a process. Although it is tempting to rush in and go wild with your charts, I strongly recommend taking the time to build a strong foundational knowledge of how Tableau works!

 

Choose the right dataset for YOU

 

I highly recommend choosing a dataset that interests you. It is easy to brush off the recommendation of ‘finding something that interests you’. Clean, detailed datasets, albeit one you mightn’t find interesting, are very tempting at first. But, if there is one thing you take away from this blog post, it should be that picking a data set that interests you! If you aren’t interested in your dataset, you won’t feel inspired to dig deeper into the analysis to discover unique insights. Remember, you will be spending a lot of time working on your visualisations, so having an interesting dataset helps keep you motivated and ever-curious. Also, it means you will enjoy working on your project! My first dashboard focused on top Spotify Songs across the years. As I was coming from a background as a professional musician, I found this dataset very interesting. This ensured I was constantly eager to find out the ‘how and why’ behind the data.

 

Look at successful Data School applications

 

The best way to learn how to do something is to copy other’s who have done it well. You can find the dashboards of successful Data School applicants in the Blog section on the Data School website. Looking through and analysing all the previous dashboards was incredible valuable – especially since I had never seen one before! This step really helped me broaden my knowledge on more complex and interesting visualisations, understand what contexts certain charts are most effective in, and how to format a whole dashboard so it looks visually clear and compelling. If you have never created a dashboard before, I recommend trying to replicate parts of successful dashboards yourself from scratch!

 

Keep it simple and tell a story

 

One of the most important things in the application in presenting the data in a clean and interesting way. This goes for both the individual charts and the dashboard as a whole. Tableau has such a wide range of tools to help create highly complex and cool looking charts, but they may not showcase the data in the most optimal way. Similarly, complex charts can also look too busy and cluttered, impeding it’s impact in supporting your analysis. Funnily enough, ‘simple’ charts like the bar chart, line chart, and scatter plot charts are extremely effective in presenting a clear story, whilst maintaining a sleek and clean look to them.

You also want to make sure your dashboard also follows a logical progression that supports your analysis. You should aim to make each chart flow on to the next; avoid having a bunch of charts that seem disconnected from each other. Find one or two strong insights, and build your dashboard around that. Having a flowing story through your analysis helps to not only keep it succinct and clear, but also lends itself to a more wholistic analysis of the data.

 

Feedback is your friend

 

Don’t be afraid to ask for help! If you are completely stuck or just have a small question on formatting, reach out to any of the coaches. After sending in my draft for the first interview, I received some great feedback on little formatting things and other functional tools I had never thought to use. I think if I hadn’t received that guidance and applied the feedback to my dashboard, I wouldn’t have had much of a chance to get through to the second round of interviews. Just remember, there is no shame in asking for help! The coaches and interviewers are such lovely people and don’t care on how much or little you know about Tableau – they just want to help as much as they can!

 

Rehearse your presentation

 

Make sure to rehearse your presentations before your interview. If you are like most people, you may find yourself getting a bit nervous in the interview, so having a rehearsed plan definitely helps to keep you on track. You only have a set time limit, so rehearsing ensures you are able to determine what to talk about in the time that you have. Also, the more you rehearse the more familiar and comfortable you are with your analysis and the dashboard. Being familiar and comfortable with everything on your dashboard means that you can present in a more relaxed way – it feels and sounds much less rigid, and helps to engage your audience. Asides from having strong analytical skills and some Tableau abilities, being able to present is another key component in the Data School.

 

Ben Devries
Author: Ben Devries

Ben graduated with a Bachelor of Music Performance (Honours) from the Sydney Conservatorium of Music in 2023. For the last few years, Ben spent his time working as a professional jazz saxophonist which led him all around the world performing in cities such as London, San Fransisco, and of course, Sydney. But despite his musical background, Ben’s interest in data analytics came from his passion for problem solving and understanding the little details of how and why things work. From there, Ben went on to discover the Data School Down Under, and throughout the interview process became further inspired not only by the logic and flexibility of data, but also the ability for data to provide valuable insights to help solve complex business problems and present meaningful stories. Ben is excited to join Data School Down Under, and hopes to utilise his creativity, improvisational skills, and ability to draw connections upon diverse areas of information learnt as a musician within his new career in data analytics. In his spare time, Ben still enjoys playing his saxophone, as well as downhill longboarding, and spending time with his family.