In the latter half of my training at The Data School with The Information Lab, I faced a unique challenge: delivering a 90-minute Power BI session, marking my first foray into teaching. Each cohort tackles this challenge, with DS42, my cohort, split between Power BI and Tableau training.
Focused on Power Query in Power BI, my session emphasized the significance of clean data for effective analysis and basic data transformations.
Choosing Power Query over Tableau (and its data tool equivalent, Tableau Prep) for the training session presented a deliberate step out of my comfort zone. Despite having fewer hours in Power Query compared to Tableau Prep, the decision proved rewarding as I became more confident with the tool's interface and transformation options as well as its limitations.
In preparing content for my lesson, I recognized that my audience would be receiving a lot of technical knowledge throughout the day, so it's unlikely that all of my content will stick. Therefore, I wanted to drive home the importance of clean data and data transformation tools and how they can streamline processes.
After going through my content with a brave volunteer, I realized that some of my content wasn’t as understandable as I hoped. Therefore, I realized that I needed to create some simpler bite-sized examples as well as cut content that focused on joining datasets.
I was also worried about my timings for the session. In my first run-through, I finished with about 50 minutes to spare. However, I knew practicing with one person is very different from 20 people, especially having no prior knowledge of people’s abilities.
I still felt it was better to be over-prepared, thus I created a series of challenges that would cover all the previous concepts in my session. I utilized the excellent Preppin’ Data Challenges, a weekly series that focuses on data transformations. However, these challenges focus on Tableau Prep, so a big challenge was to strike the balance between challenge difficulty and feasibility in the Power Query Software.
Fortunately, the base content I prepared aligned perfectly with the 90-minute slot, allowing us to cover only one Preppin' Data challenge. This mirrored the experience in our Data School sessions, where coaches often adapt to address specific challenges rather than completing their entire planned content. This made me realize the importance of educators, coaches, and trainers mastering the art of preparation, occasionally needing to think on the fly and address unexpected questions to enhance individual learning experiences.
What's great about these sessions is you also have the rest of your cohort and another coach in the room for support. You are not in the room alone. Troubleshooting and answering questions during the session occurred more frequently than anticipated, reinforcing the value of teamwork!
Overall, I felt this project has greatly improved my confidence in teaching as well as presenting to unfamiliar people. I also felt that going outside of my comfort zone led to a greater appreciation for Power Query.
If I had any advice for future DSers, it would be to understand that your audience won’t remember everything, so stick to core concepts and why your software is important. It is also important to have a good amount of content; it's always better to overprepare than underprepare! Finally, you’ve got to practice your content with someone who has no prior knowledge; this was pivotal in understanding what people will latch onto or miss.