Data visualization is the process (or the process output) of communicating key aspects of a dataset through the use of “visual elements like charts, graphs, and maps,” among others.[1] Given the complexity of contemporary datasets, especially those related to Big Data, the role of data visualization in business intelligence, data analytics, and managerial decision making is becoming increasingly important. While many software programs offer some elementary suite of data visualization tools, like Microsoft Excel, flagship visualization tools include Tableau and Qlik.[2] Data-science friendly scripting languages such as Python and R also have various libraries for creating advanced visualizations.[3][4]
At the most basic level, a data visualization must articulate some trend or component of a dataset in a way that is unambiguous to the users. Great visualizations, however, “are quick to decipher and easy to be remembered as well as being appropriate to the data they represent.”[5] Because data visualization is very user-centric, there is no closed-form solution when it comes to designing visualizations. However, all visualizations should tell a story, provide sufficient context without overwhelming the user, and elicit a call to action.[6] The latter principle is especially important because “The more easily understood your call-to-action, the more people will willingly interact with your insight, brainstorm solutions and implement recommendations.”[6] In regards to the technical principles, most data visualizations should include a baseline, “sufficient contrast between colors,” a limited number of colors, clear and concise labels, and intuitive ordering.[7]
Businesses use data visualization techniques to create dashboards “that track company performance across key performance indicators and visually interpret the results.”[2] For instance, IT call centers use dashboards to convey information regarding agent handle time, rate of service ticket closure, and average client feedback rating. Using these dashboards, managers can determine which agents should be given a raise for their job performance, and which agents require more training to boost their performance.[8] In a broad sense dashboards and data visualization techniques also serve to enforce transparency and accountability. In 2016, the White House released an interactive treemap representing the Federal Budget. The goal of this visualization was “to communicate with taxpayers about where their tax dollars would go.”[9]
Data scientists and machine learning architects use data visualization techniques to visualize the performance of Deep Convolutional Neural Networks during network training. During each training epoch, a set of metrics is computed including metrics like training data and validation data loss and accuracy. However, drawing conclusions from any one epoch is meaningless as the metrics in that epoch could correspond to an overshot model or other random processes in the model development. Instead, it is important to analyze and draw conclusions from the overall trend of the metrics. Multiple line graphs provide machine learning practitioners with a quick, reliable way of doing this; without them debugging complex models would be difficult, if not impossible.[10]
Many bioinformatics programs like those offered by Geneious and Dnastar include visualization tools that allow biologists to examine 3D models of DNA, proteins, and other molecules.[11][12] Furthermore, medical students, practitioners, and professors are now using apps like Human Anatomy Atlas by Visual Body to visually examine the complex networks of the human body for training, disease and injury diagnosis, and medical equipment engineering.[13] Among other features, the interactive visualizations found in Human Anatomy Atlas allow users “see structures from all body systems,” “delve into the microanatomy of tissue and special organs,” and “watch muscle movements demonstrated in rotatable moving 3D models.”[13]
Data visualization is changing the way political scientists and the general public analyze political policy and climate. One day after President Trump’s 2019 State of the Union (SOTU), American news site Axios posted a news article summarizing the Trump’s SOTU talking points. The article includes a massive interactive visualization which features his speech overlaid with various colors, each of which corresponds to a distinct topic.[14] For starters, this visualization allows users to quickly identify topics they care most about and examine the President’s words verbatim. However, from a big picture, it also allows users to gauge the amount of time the President talked about each topic. Whatsmore is that the 2019 SOTU transcript is placed alongside the 2018 and 2017 SOTU transcripts (also color-coded) allowing users to compare the President’s agenda over time.[14] This type of visualization demonstrates how complex data can be converted into a comprehensive and visually-appealing graphic that allows users to “drill down” into data as they see fit.
Sources
- https://www.tableau.com/learn/articles/data-visualization
- https://searchbusinessanalytics.techtarget.com/definition/data-visualization
- https://www.analyticsvidhya.com/blog/2015/07/guide-data-visualization-r/
- https://mode.com/blog/python-data-visualization-libraries
- https://www.tapclicks.com/innovative-data-visualization-examples/
- https://www.gooddata.com/blog/8-ways-turn-good-data-great-visualizations
- https://www.columnfivemedia.com/25-tips-to-upgrade-your-data-visualization-design
- https://www.klipfolio.com/resources/dashboard-examples/call-center
- https://www.tableau.com/learn/articles/best-beautiful-data-visualization-examples
- https://medium.com/@kapilvarshney/how-to-plot-the-model-training-in-keras-using-custom-callback-function-and-using-tensorboard-41e4ce3cb401
- https://www.geneious.com/about/
- https://www.dnastar.com/software/structural-biology/
- https://www.visiblebody.com/anatomy-and-physiology-apps/human-anatomy-atlas
- https://www.axios.com/what-trump-talked-about-in-the-state-of-the-union-803bc486-d1b9-4817-933d-172735103b46.html
johnfantell 