Technology Advances

Technology for data visualization has come in many forms over the years. It’s not limited to only the use of computers. It can also be advancements in science, mathematics, or even typography. Advances in these areas helped to advance the field of data visualization. However, when computers arrived in the 1950s and 1960s, the proliferation of data was available at such a rate. Then, when personal computers arrived in the 1980s, the advancement of computer models made it easier to represent and present the data visually. With the advent of new technology comes great responsibility. Now, let’s look at some pros and cons regarding technology advancements.

Pros & Cons

Think about your manager asking you to present the new use of AI voice-over in developing your courses. Your manager wants you to show the Leadership Team (LT) how using AI voice-over is more efficient than traditional methods. You have a week to prepare. You’ve already been collecting data about how AI voice-over provides an efficiency increase of 45% comparatively. Because you have the data in an Excel spreadsheet, technological advancements can assist you in getting a quick comparison chart. Great, but remember you’re trying to convince LT to approve the budget for this new technology. A simple comparison chart doesn’t tell them everything. It would be best if you built a story. While tools like Excel only get you so far. You still need to create an appealing visual design. According to Tableau, “Sometimes people can accidentally (or even purposefully) misrepresent data.” (Tableau, 2024) Therefore, it’s essential to not rely solely on technology.

Good Charts – What are they?

Good Charts should be simple to understand. You should be able to digest and see the information the chart conveys quickly. Is it a comparison of data, or is it showing a trend? Knowing which chart to use when another piece of a chart is good. Using a pie chart is not helpful when showing a trend or pattern. Another piece of the good chart puzzle is having a good legend. Let the audience know what the data is and what the critical pieces of data are.

Appealing Charts

I’m visual, so accounting or statistical data alone isn’t enough. I need to see correlations, patterns, etc. Additionally, I’m a gamer. How does that fit into data visualization, you ask? Well, gaming (computer, console, etc.) has prominent storylines and minigames built into them. Take, for example, one of my favorite games, Diablo IV. It would be boring if you were to play this game only using dice, a tally sheet, and story cards (think old-school dungeons and dragons). Enter in advancements in computer graphics and you have player maps of the places you’re visiting, you can design your character based on visual queues of skills and attributes. This visual representation of computer databases allows me to build the best Druid or Sorcerer class character to defeat the monsters at the next level!

In my other favorite game, Star Citizen, a Heads-up Display (HUD) and Mobiglass charts provide the player with critical game-making data to act on.

Conclusion

Data visualization can tell a story that text and numbers alone cannot. Today, more than ever, there is access to many data points. Charts and graphs, while good, are only as good as what they were meant to convey. Before you begin visualizing data, a crucial piece of the data visualization journey is to know the story you want to tell. Then, with that story in hand, collect, and analyze the data. Understand what the data is conveying and which visualization best supports it. Then, be selective when choosing one visualization type over another. Finally, ensure you remain objective to allow your audience to digest and see what the data says.

Resources

Data Visualization – a complete introduction. HEAVY.AI. (n.d.). https://tinyurl.com/DataViz-HeavyAI

Hazzard, E. (2024, February 25). Data Visualization in games. GameAnalytics. https://gameanalytics.com/blog/data-visualization-games/

Sridharan, M. A., & Friendly, M. (2024, January 20). History of data visualization. Think Insights. https://thinkinsights.net/data/data-visualization-history/

Tov-Ly, G. (2023, October 26). Diablo IV’s Amazing launch: Data analysis by Overwolf. Medium. https://tinyurl.com/DiabloIV-DataAnalysis

Wang, L., Wang, G., & Alexander, C. A. (2015, July 22). Big Data and visualization: Methods, challenges and technology progress. Digital Technologies. https://pubs.sciepub.com/dt/1/1/7/

What are the advantages and disadvantages of data visualization?. Tableau. (n.d.). https://tinyurl.com/Tableau-DataViz-Adv-vs-Disadv