As we wind up the final week of training, there is a sombre mood amongst the trainees in DSAU7. The 15 weeks leading up to this moment has felt both simultaneously long and incredibly fast at the same time. It’s safe to say that everyone has learnt a lot, not just about Data but about themselves and each other. All of us had no idea what to expect when we signed up but we have all been blown away by the course and the training we’ve received. To cap off this huge 4 months, here’s a retrospective of the program and my experience at The Data School.


The Training (Technical)


When I first applied, I had never used Tableau or even heard of Alteryx. As with everyone else, I had no background in IT or data analytics. I spent a couple hours learning the basics of Tableau just to submit an application with no idea how I would go. Now I can confidently say that I am proficient in all things Tableau and Alteryx.


The training offered by our coaches is both extensive and incredibly detailed. We are trained in everything Tableau and Alteryx as well as other relevant programs such as SQL and Power BI. The training is not easy, and will require lots of quick learning and self-revision as there is a lot to cover. However, the support from the coaches, your cohort and wider MIP staff is phenomenal and there is help and support at every point to help you.


The Training (Soft Skills)


Besides the technical side to Data Analytics, the soft skills to being a consultant are arguably more important. It is here that you really hone your abilities to present, ask the right questions and consult. The client projects are a constant source of experience in project management, leadership and a look into consulting. There is so much gold to pick up through the non-technical teachings peppered throughout the course that are just as important. As we progressed through the 16 weeks, I could see the confidence rise in our consulting abilities.


Client Project


The client projects (while intimidating) have been the absolute highlight of the program. I gained a huge amount of experience that was instrumental in making us better Data Analysts and consultants. Everything from project leadership and management to the execution of our training in data analysis and visualization was required. We went through the highs and lows during these weeks as we battled through difficult problems and conflicting ideas.


We were exposed to a wide variety of industries and problems covering tax, insurance, supply chain and agriculture to name a few. Everything that we had learnt needed to be applied and we started to see where the soft skills are just as important as the technical skills. I loved every single minute of these challenging weeks, allowing us to really exercise our problems solving abilities as well as our presentation skills.


The Cohort


Last but not least is the cohort experience itself. When you spend every day with a group of 7 other people, you are bound to become a lot closer. A mutual connection is formed through the challenges and struggles of training and client projects. What you’re left with after is more than just data analytics skills but a group of friends to continue this journey with into placements. Another aspect that makes the experience great is the connection with the wider MIP staff. There is such an approachable and friendly atmosphere to the company that makes networking and asking for help easy.




I am immensely grateful for the opportunity that is the data school training. I would not hesitate to recommend and encourage anyone who is mildly interested in Data or visualization to apply and go for it. There is nothing but good things for your future career in Data through this program! Please feel free to connect with me on Linkedin and shoot me a message if you have any questions.



Jason Yeo
Author: Jason Yeo

Jason is originally from Malaysia and has lived in Hong Kong and Australia. He holds a Bachelor Degree in Actuarial Studies and a Bachelor in Commerce, majoring in Business Strategy and Finance at UNSW. He has a passion for problem-solving and data analytics, hence he decided to pursue a career in this industry and pivoted into the Data School. In his free time, he enjoys sports, going to the gym and he likes music and playing his guitar.