In year 1.2, we had a data visualisation module named Data Visualisation and Discovery in Ngee Ann. In that module, we got to learn how to visualise vast datasets with Python using numpy, pandas, matplotlib and seaborne, and we got to learn how to learn PowerBI with Power Query and Power Pivot, building on our knowledge of those 2 tools from the fundamentals in data science module the semester prior.

While the process of learning PowerBI itself proved to be difficult (especially things like Measures of which there was no mention of in Year 1.1), using it during the assignment proved to be quite stressful, but also quite fun!

Some context about the assignment

The assignment centers on social and environmental sustainability within the ASEAN region. Specifically, it looks at issues aligned with the United Nations Sustainable Development Goals (UN-SDGs) 11, 12, 13, 14, and 15. A key requirement is to use data-driven proposals to compare Singapore with at least one other ASEAN country.

To successfully complete the project, the assignment requires the following steps:

1. Data Sourcing & Prep: Gather relevant datasets from reliable sources, preferably containing hundreds of rows. The data must be cleaned and prepared for analysis , and accompanied by a data dictionary and proper citations.
2. Exploration: Identify meaningful exploratory questions from the dataset to guide the analysis.
3. Visualisation & Storytelling: Design a multitude of visualisations to effectively derive answers to the exploratory questions. Ultimately, these visuals must be compiled into a dashboard to perform data storytelling and propose solutions to the discovered issues.
4. Broader Impact: The project aims to promote ASEAN awareness and encourage reflection on regional interconnectivity and socio-economic development.

What I decided to do for this assignment

After not minding the assignment for half of the assigned time, it struck me that I only had about 2 weeks to complete a whole report, along with a Data Dictionary and a PowerBI report file. As such, I decided to begin 2 weeks before the deadline (while I could've definitely started earlier late is better than never, but I shouldn't leave out on precious time like that).

I decided to investigate on the EV adoption rates of Singapore and Malaysia. EVs are seen as a great way to decarbonise the transport industry. On top of that, I also decided to investigate on what would support this transition: the Energy sector. The Energy and Transport sectors work hand-in-hand to decarbonise. If only the transport sector moved to decarbonise by switching to EVs, but the Energy sector still used predominantly natural gas and coal, it would not yield any benefit to switching to EVs since EVs will rely on the grid for electricity, but the source of energy of the grid is still not clean.

A minor hiccup that I hit

While I was working on this assignment, I found that my writeup was low quality, and as such I decided to rewrite that report. While it definitely consumed more time that I had hoped, I was thankful that I did because sometimes starting from scratch is much easier than editing what you already have. Starting afresh is easier than starting from a mess.

Apart from that, the assignment went relatively uneventful. While I felt that my dashboards could have had more flare, they definitely encompassed the data that I wanted to present which is an infinite more times important than styling.

What I learnt

I definitely learnt a lot about PowerBI, but this assignment also taught me quite a bit on how to present the data and do proper data storytelling. For example, why did I decide to research on EVs and Energy, what are the key statistics and KPIs and what they mean, and what this means as a whole for Singapore and Malaysia, and also recommendations on how both countries could continue transitioning to a greener future

Overall, I found this assignment really fun (also due to the almost non-restrictive nature of the assignment), but time management is especially important for these kinds of assignments since it can be difficult to know where to start, and that extra time is crucial to getting a quick footing in an assignment where the set boundaries are quite large.

— Sairam