Let’s take a look at what it took to get in to our latest cohort, DSAU27!
If you are interested in joining one of our future cohorts, this is a great chance to see what kind of visualisations our successful applicants produced. I’ve shared some comments about what made their applications stand out.
If you’re interested in joining one of our future Data School Down Under cohorts, find all of the information you need to apply here.
Amy Ellis
Amy holds a degree in Genetics and a Postgraduate Certificate in Education. She taught biology for over five years before realising that the most fun she had was when she had to go over educational data and use them to draw insights on student performance. This realisation motivated her to complete a few online courses, leading her to a new career path in data analytics with The Data School was the path for her.
Outside of work, Amy enjoys weightlifting and squash, and works hard to keep her Animal Crossing island tidy and welcoming.
Amy produced a very informative, report-style dashboard. She used lots of questions and provided key insights alongside the charts.
Don Kang
Don is an experienced Mechanical Engineer with a diverse background in academic research and engineering. He is skilled in Python and SQL, data ETL/ELT and cloud platforms like GCP, AWS and AZURE. He is also detail-oriented and quick to adapt to evolving business needs and industry trends, with a passion for leveraging data to drive decision-making and innovation.
Don enjoys multiple sports such as football, baseball, tennis, cycling and swimming.
Don picked out a particular story by focusing on one state against the national average. He used simple charts to effectively highlight the causes of fatalities in a very impactful way.
Troy Stephenson
Troy holds degrees in Science, IT, and Education. These have equipped him with a multidisciplinary foundation combining analytical thinking, problem-solving, and technical proficiency. During his graduate studies at CSIRO, where he analysed genetic sequence data and gene expression profiles as part of a broader research project, he developed a deep interest in uncovering insights through data.
After several years as a STEM educator, Troy has transitioned back to being data-focused, bringing a unique perspective shaped by his teaching experience and ability to convey complex ideas effectively. His skills cover the entire data lifecycle, from data cleaning and analysis to creating effective visualisations that support decision-making.
In his free time, Troy enjoys trail running and staying active, relishing the chance to clear his mind and explore the outdoors.
Troy took a different angle than others by looking into the online presence of charities. He also found an interesting way of showing the differences in charitable programs ranking by size of charity.
Nisha Ahamed Ibrahim
Asharaf Nisha holds a Bachelor’s degree in Information Technology and has worked as an Ecommerce Analyst for four years. Throughout her career, she became fascinated by the insights that data can uncover and the impact it can have.
This passion led her to pursue a career in data analytics. To strengthen her skills, she completed the Google Data Analytics Professional Certificate, where she gained proficiency in Tableau, ultimately guiding her to The Data School. In her free time, Asharaf enjoys reading and traveling.
Nisha provided clear insights in a very structured, well-designed flow. She shared many insights and rounded off with clear suggestions for the audience.
Yashada Kulkarni
Yashada has a background in ecology and biodiversity. For her PhD, she studied pheromones in butterflies. When she wasn’t chasing butterflies in the field she was analyzing data in the lab.
Apart from being a researcher, she has worked as a biodiversity and sustainability professional with corporates. Having worked extensively with data in her previous roles, pivoting to data analytics was an obvious choice for her.
In her free time, she likes to go bird watching and reading latest advancements in Nature Tech.
Yashada used questions well to make it very clear to the audience what they are looking at. Her clean charts made it very clear what her insights were.
Augusto Terra
Before joining The Data School, Augusto was a PE teacher and Football coach. Augusto holds a Master’s Degree in Exercise Science from the Federal University of Rio de Janeiro, it was through his studies that he developed his passion and enjoyment for working with data. This led him to pursue a career at The Data School, where he is eager to explore diverse data sets and deliver meaningful business solutions.
Outside of work, Augusto enjoys spending time with his friends and playing football.
Augusto structured his viz in a way that meant it is very clear what we are looking at and what the main takeaways are. He also brought in some information on actions authorities are taking to help supplement his insights.
Darby Lehane
Darby Lehane graduated from Chancellor State College, being selected as an ambassador whilst competing internationally in a robotics team and placing second in a debating tournament.
He finished his first year at the University of Queensland studying a Computer Science/Master of Data Science dual degree and intends to finish his studies at the University of Sydney. Before The Data School, he worked three years as a Service Supervisor for Woolworths while studying at high school and later uni. He enjoys coding and is proficient in Python, SQL, Java, and Matlab.
Darby found an interesting story within the data looking specifically at donation proportion of total revenue by the charity size.
Kyle Stanford
Kyle holds a Masters in Teaching, specialising in mathematics and physical education, from WSU. After starting his career as a teacher’s aide and later as a teacher, he shifted to data analytics to explore the world beyond education. With a strong passion for problem-solving, honed communication skills, and an eye for visual design, data analytics has become a natural next step in his career.
Outside of work, Kyle participates in a variety of sports, including martial arts, but also enjoys more relaxed hobbies like gaming, anime, and music.
Kyle’s dashboard had a simple message about how to reduce the number of accidents. He used clear insights and recommendations to help the user make decisions.
What Can Future Applicants Learn?
Once again, this cohort reminded us that the best dashboards aren’t just beautiful — they’re thoughtful, well-structured, and tell a story. Here’s what worked well for DSAU27:
- Tell a Clear, Focused Story
Successful applicants often picked one specific angle or narrative within the dataset rather than trying to cover everything. This made their insights more impactful and easier to follow.
- Use Structure and Questions to Guide the Viewer
Dashboards that were well-organised and included guiding questions helped direct attention and made the user experience more intuitive.
- Prioritise Clarity and Actionable Insights
Clean visuals paired with clear, well-explained insights or recommendations made dashboards both informative and decision-friendly.
If you’re thinking about applying, check out our blog or explore the visualisations on Tableau Public. You don’t need to be perfect; just passionate, thoughtful, and ready to learn.
