How to Excel in Data Visualization?
A short story on how I answered this question thru data.
One of the main skills needed in data science is data visualization. Data visualization is the graphical representation of data and information. This skill is fascinating since you will present your insights in an organized and creative way by covering both technical and art at the same time.
While I was creating visuals during my previous courses, there are times that I encountered difficulties and challenges. A question started to formulate in my head that I need to find an answer to. The question is “How to excel in data visualization?”.
During our first assignment in dataviz class, the data provided to us is about the 2020 survey census from Data Visualization Society. As early as now I wanted to think and act like a data scientist, that’s why I took this opportunity to answer my question. According to their website, the main goal of the survey is to build an understanding of who the people are that identify as part of the data visualization field, how they work, and what their challenges are.
While I was going thru the datasets, there are new questions starting to pop up in my head that can help in order to find the answer to my main question. After a series of tasks, the following are the insights I had mined in the dataset:
- How do they learn data visualization?
In figure 1, a treemap was used to visualize how the respondents learn data visualization. Based on the chart we could see that “Mostly Self Taught” category has the darkest color among them. We can say that most data visualization specialists who answered the survey studied data visualization at their own pace.
2. What technologies do they use?
In displaying the most used categories within the dataset, a word cloud chart is best to use. Aside from it is simple, it can easily inform the viewers you’re main objective. In Figure 2, we can easily tell that the most technologies used by the respondents are Excel, Tableau, R, and Python.
3. What are the methods to develop data visualization skills?
From the bubble chart that was presented in figure 3, we can already identify the information we needed by basing thru the diameter of the circles. The most helpful methods that were identified by the respondents are Project Application, Examples, and Video Tutorial.
Analyzing the information we gathered…
From these, we can conclude that if an individual wants to excel or learn data visualization:
- Individuals must have a driving passion to learn data visualization.
- Consider learning data visualization tools such as Excel, Tableau, R, or Python.
- Project applications, examples, and video tutorials are helpful to develop data visualization skills.
Hello Dear Reader! I hope you’ve enjoyed reading my first story here in medium :) Hope this could help in your data science journey.