I wrote this reflective essay after completing a data visualization course.
Technical Skills
I mastered powerful technical skills for visualization in this course. In Tableau Prep, I learned how to clean the data. For example, since Tableau prefers “tall and thin” dataset, I can “pivot” the survey data. In Tableau, I learned how to use dimensions and measures to create wonderful graphs in a single sheet. Moreover, I can build a dashboard by existing sheets and make special connections for them Furthermore, I learned how to create a story and lead viewers to go through all my visualizations in a logic order.
Sense & Philosophy of Visual Art
Now, I become capable of creating a good visual art and judging whether a visualization is great based on the aesthetic theories and visualization principals I learned. For example, according to Shaffer, a visualization should be clear, clean, concise, and captivating. I gradually realize that, on my visualization, I should always ask what else I can remove further rather than what else I can add on. Similarly, I should follow data-ink theory to avoid visual redundancy. Moreover, I learned how to leverage colors in an appropriate way and I understand that I should put the most important thing on the upper left and put those that are not important on the lower right.
A Science of Communicating Truth
As Maureen Dowd said, “Never before have we had so many tools to learn and to communicate. Yet the art of talking, listening, and ascertaining the truth seems more elusive than ever in this Internet and cable age, lost in a bitter stream of blather and misinformation”. In the era of ‘big data’, there is a unprecedentedly huge demand for interpreting data and communicating the truth. However, “the larger the island of knowledge, the longer the shoreline of wonder”. Every graphic designer should spare no efforts to stick to the truth or prompt exploration of truth. Inevitably, there are many people use some techniques to mislead others for their own interests; however, those behaviors are intolerable.
Therefore, when designing a graphic to explain something, getting the information right comes first. Moreover, information should be structured in a way that helps understanding. Graphics is a real cognitive aid. I should choose different types of graphs that matches the information I present. For example, there are specific graphs designed for comparison, distribution, relationship, and composition.
Achievements
I think I have two great achievements here. The first one is to deconstruct a difficult dashboard and now I am confident that I am capable of deconstructing every dashboard in front of me and improve that based on all the visualization principals I mentioned above. Second, I used Tableau Prep to deal with the survey data and I self-learned how to Gantt bar to illustrate Likert Scale Questions and how to create a story for readers. Now, for any questions about tableau, I have the capability to search for an answer directly from their website.
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