And so we’ve come to the end of 16 weeks here at the Data School! Even though we’d been warned how quickly time would fly, it’s still surreal to go through it all. Reflecting on how far we’ve come, I decided to revisit some goals I’d set myself in Week 1…
1) Make good use of resources, practice and don’t be afraid to ask for help.
2) Keep asking the why and so what questions and focus on the big picture.
3) Be flexible and open to feedback.
Looking back, I think these points quite aptly summarise the whirlwind of a time here training at the Data School…
1) Learn as much as you can
It’d be difficult to overstate how much we have learnt in this short span of time. All of us going from minimal Tableau and no Alteryx experience to being certified in a matter of weeks is a testament to the level of teaching we were immersed in each day. I benefited greatly from the coaches and MIP staff who pushed us to explore and experiment, and offered invaluable wisdom, both technically and in preparation for work beyond. And as an added bonus, doing this all alongside a team of data schoolers who are highly motivated, intelligent (and I guess alright company). I learnt a lot from seeing the different ways they tackled problems, and sharing tips and tricks with each other along the way.
Another thing that amazed me early on was the extent of knowledge available on the wider online community (the challenges, forums, public galleries, etc). I would encourage future cohorts (or even anyone interested in applying) to get stuck into these as much and as early as possible. I often found it challenging to balance and make time for this ‘extra-curricular’ learning, especially as the intensity of client weeks ramped up. But there is definitely value in keeping up and trying to continually add to the repertoire.
2) Ask questions, understand the purpose, and find stories to tell
Training at the Data School is not just about learning to produce pretty dashboards. I was constantly challenged to think more critically about the purpose and functionality of what I produced. This intentionality is key in all stages of the production process…
We quickly realised the importance of asking better questions, early on. This was especially evident during client weeks, where an effective requirements gathering and asking the right questions could really set you up well for the week. Clarity around the motivations and criteria for a project are key to producing an effective final product.
Then through to data preparation, where we learnt how to explore and interrogate data more efficiently. As we gained experience, we could more quickly determine what tools to use, and how to connect, structure and format our data to answer the questions at hand.
Of course we invested a lot of time learning visualisation best practices and how to communicate data effectively. Along the way we also picked up many techniques (such as parameter and set actions) that would boost the interactivity and overall experience of our dashboards.
And finally down to presentation, we learnt tips on how to package our presentations and confidently hand over our work. It is often easier to focus on the technical aspects of what we have developed, but through constant practice and refinement, we were encouraged to invest more efforts into drawing out insights our audience may not even be aware of.
That is not to say that we have completely mastered any of these things. It is still easy to fall into the trap of simply whipping up charts and placing them side by side to tick all the boxes. But having gone through this process each week, whether it be through training exercises, internal Friday presentations or client weeks, this rhythm has become more natural and of priority.
3) Be ready to adapt
Going through client project weeks, one thing that was immediately apparent is that things change, constantly. The project requirements and scope may be adjusted, business rules may not be what we initially thought, the data may not be there to address the questions we set out to answer. So key takeaways through all this were learning to be flexible, and practical problem solving experience. I think a key advantage in the training is gaining the confidence and experience to know when to change directions, and what else to try when things aren’t working. Of course, this is still a work in progress, and something I look forward to building upon as we venture into client placements.
So as you can hopefully see, the last four months have been an incredibly challenging, steep, yet rewarding learning curve. I look forward to much more learning as we step into the next stage of our adventure here at the Data School!
Image source: lifeforstock (www.freepik.com)