Data Visualizations and Narratives Fall 21

Displaying performance through a benchmark gives context to data and shows how well they meet expectations. Often displayed as simple graphs, it is no wonder that they accompany news articles, a place where ease of comprehension is paramount.

In an article from 2018, Drew DeSilver from the Pew Research Center examined the purchasing power of the average wage throughout the past five decades. DeSilver used text to describe the statistics and their implications. Additionally, he included a graph that compares the dollar amount to its equivalence in 2018.

… today’s real average wage (that is, the wage after accounting for inflation) has about the same purchasing power it did 40 years ago. And what wage gains there have been have mostly flowed to the highest-paid tier of workers.

Drew DeSilver, Pew Research Center, August 7. 2018

Though incidental, this graph sees the line for “Constant 2018 dollars” acting as an average or standard, both potential facets of focus Stephanie DH. Evergreen describes in Effective Data Visualization. Through it, the audience can see how the two values compare and their trends: whereas “Constant 2018 dollars” has, indeed, remained relatively constant since 1964, “Current dollars” has continuously grown, narrowing the gap to a point.

Other examples can be more cut-and-dry. Isaiah Mitchell reported on end-of-year exam results for Texan public schools in a 2021 article. The report included several graphs, most of which compared grade averages in Texas to their national counterparts.

The data is self-explanatory, a testament to how well it is suited to the graphic. It is clear to see the progression of both averages and the overall decline in Texas’ marks.

Comparisons to a benchmark are not exclusive to news articles, however. An example that might be more familiar to students, in particular, might be their results of standardized tests.

Here, the comparison is more obvious. The graphic takes the liberty of even labeling the benchmark for both areas that were tested. This makes it even easier for the viewer to determine how well they fared relative to what is deemed “on track for college readiness”. In Effective Data Visualization, this style best reflects a “bullet graph” (page 105). There are distinct acceptable and unacceptable areas, a target line (seen here as the transition from yellow to green), and the actual value depicted as a dot.

Though their forms may vary greatly, the purpose benchmarks serve is the same. As evergreen put it, their stories “… help a reader to determine whether performance was good, bad, or close to the mark,” (page 91). They offer necessary information for an audience and gives a data set an easy-to-understand meaning. As previous examples showed, complex, sometimes convoluted information can be well displayed through a benchmark.

These are three benchmark data visuals below that discuss the same idea. Each one presents statistics around advertisements, marketers, brands, etc, however, they all are presented in different ways.

For example, the very first one displays several kind of content brands use to reach out to consumers. Videos, emails, and more are the categories that are shaded in different colors with different percents, since brands may use on for the other or even multiple. Overall, the main discovery of this benchmark is how videos help brands get their idea/products seen and sold out to the world.

Marketing for Social Media

Now, the second benchmark also has numerous categories catered to a similar idea, which is the ways marketing on social media can help. The top is increased exposure of the business, but what is different in compared to the last is the 3D model. Not to mention, this benchmark inserted the percent(%) throughout the grid to help viewers read the numbers and compare the numbers easier.

As for the last set of data, this one separated the age groups along with genders for who uses social media for brand research. Here we just have two colors, the red and the orange, that separate females and males, all in 5 age ranges. Viewers can notice the drop in social media brand research the older people get, as well as the usual audience of each group, asides from ages 55-64, being females. The data labels are also put above the benchmarks throughout, which is another way each of these graphs differ from one another. In conclusion, there are various ways to construct and/or explain topics in the form of a benchmark, even with little changes to the color, labels, angles, etc.

160+ Social Media Statistics Marketers Need in 2024

Piktochart

URL: https://piktochart.com/features/comparison-chart-maker/

Piktochart is a free comparison chart making website for the basic user. In order to access their templates, the user must already have an account through Google or by simply signing up for free. By creating an account, the user is given a folder to store their creations which is useful for later editing and storage. The website offers demos to the user to help format their data to their benefit for a more efficient comparison.

Adobe

URL: https://www.adobe.com/express/create/chart/comparative

Adobe Spark is another free comparison chart making website. Adobe is a trustworthy computer design company that has put out many other editing programs i.e. photoshop, acrobat, and animator. The user can sign up through Google, Facebook, or any email. It also allows schools to set up student accounts for school assignments and projects. Adobe offers a more customizable and free range interface as it requires more creativity from the user and how they want to present their data to the viewer.

www.dummies.com/education/math/basic-math/compare-numbers-using-a-bar-graph/

This graph does a good job of comparing two different vacation packages from the same company. Here we can compare the companies sales from their different Canada offices. Something like this would be used as a way for a company to improve itself, and the bar graph is good for visualizing the data.

What is Data Visualization?

Presenting data in visual graphics such as charts, maps, graphs, etc. to create both an appealing display and to allow the audience to easily understand the information presented

Two Ways To Present Data Visualization

Static: Printouts or web data that limit the viewer to only see and explore the data that is presented at the initial sight.

Interactive: Web data and multiple printouts that allows the viewer to engage in the information by providing various categories and hyperlinks to expand the information for better understanding

Finding The Best Fit

The first step in using data visualization is choosing the right one that will display your data in the appropriate manner. If you choose the wrong one can lead to misinterpretation of your data. These examples and breakdowns of known visualization will help you choose the best one for your data.

Line Chart_{^{(Display Trends)}}

They demonstrate an overall trend precisely that is hard to misinterpret. Good for showing trends in different categories over an extended period of time to support comparison

Bar Chart_{^{(Simple Break Down)}}

Great for displaying various values using color coded categories in a horizontal direction. Compared to a line graph you are able to add a specific category to break down the difference in better detail when you have a broader ray of data.

Column Chart^{_{(Compare multiple)}}

This is similar to a bar chart but is used bars in a vertical direction. This easily allows you to compare various data over time.

Pie Chart_{^{(Proportional Data)}}

This is a great choice when displaying percentages or specific numbers in an overall comparison of each other. Each part of the chart must come together to sum up and overall total. In order to create organization and understanding you should only use six categories or less.

Area Chart_{^(Comparison)}

Very similar to a line chart, however the areas are completely filled with a color to represent each category. This way each area I stacked on top of each other to better show the comparison. This visualization can be best used to show relative values over a time period.

Pivot Table_{^{(Quick Summary)}}

This is a very popular yet simple ways to show data using visualization. Allows you to quickly summarize, assess, and organize large amounts of data while allowing you to customize your colors, fonts, and focus points of the data as needed to appeal to your audience.

There are many various data visualizations to choose from, however it is important to remember the purpose of the chart to show the best way to display your data in an effective and appealing way to the audience. There are also many free and subscribed softwares you can use based on your skill level that will allow you to create these charts, add your own data, and customize it appropriately such as.

Google Sheets, PowerPoint, Canva, Microsoft excel, etc.

When presenting raw data in a document, it can be overwhelming for the reader and the message may not be communicated effectively. This is where data visualizations come in to make it easier to understand the relationship and meaning of a data set. To demonstrate, the analysis of electric vehicles can be used when compared to internal combustion engine (ICE) vehicles.

Electric Vehicles vs. ICE Vehicles

According to a study done by the Idaho National Laboratory, “… the distance that can be traveled for a fuel cost of $1.00 is more than twice as far with an electric vehicle” (INL). To visualize this comparison, they created a graphic that easily communicates this idea;

As electric vehicles have improved over the years, the market share for such vehicles has grown along with them. In a quarterly report by electric car manufacturer Tesla, they created a great infographic for their market share growth in different countries;

Comparing numbers can be difficult, but as seen in this example with electric vehicles vs. internal combustion vehicles, data visualizations can help bridge the gap and quickly relay a valuable message.

First let’s break down what your Macronutrients. Macro means a large scale and nutrients are a substance that provides nourishment and energy to the body; so to put that together macronutrients are the four categories of nutrients our body mostly gets our energy from. These three main categories include:

-Carbohydrates

-Protein

-Fats

-Fiber

While all of these building blocks are important when it comes to over all health protein is found to be the most effective macronutrient.

Below is what happens when protein intake is low, daily nutrients are low. There is a high percent of carbs but carbs are not a long term energy source because their expenditure is short and fast, while protein gradually gives you supplemental energy through out the day.

When it comes to protein calorie density is usually less while being more filling and fulfilling in energy.

All of the food above has 150 kcal but vary in protein and it is apparent what macro group is lacking in the important nutrient. Carbs. Many people refer to carbohydrates as empty calories, there is usually no benefit besides quick short bursts of energy. That doesn’t mean all carbs are bad tho less process carbs are good for athletes who need those bursts of energy right before a race or game.

Macronutrients may seem hard to understand when you’re not a dietician but with easy to read infographics and sites that provide them like

https://optimisingnutrition.com/macros-vs-micros/

the concept of nutrients no longer seems as hard.