Data-Driven Storytelling: Visualize & Communicate Impact

Data visualization is the process of creating graphical representations of information. This process helps the presenter communicate data in a way that’s easy for the viewer to interpret and draw conclusions.

• Reveal patterns, trends, and findings from an unbiased viewpoint

• Provide context, interpret results and articulate insights

• Streamline data so your audience can process information

• Improve audience engagement

There are many different techniques and tools you can leverage to visualize data, and you want to know which ones to use and when. Let’s recap some of the most important data visualization techniques all professionals should know.

• Tables: a set of facts or figures systematically displayed, especially in columns.

• Graphs: a diagram showing the relation between variable quantities, typically of two variables, each measured along one of a pair of axes at right angles.

• Diagrams: a simplified drawing showing the appearance, structure, or workings of something; a schematic representation.

• Charts: a sheet of information in the form of a table, graph, or diagram.

Knowing when to use certain techniques is just as important as understanding definitions. We’ll take a look at different ways to represent data and the best scenarios to use them in the next couple of lessons.

Let’s review the different types of graphs from this lesson:

• Bar graph: A graphical representation of information that uses bars that extend to different heights to depict value.

  • Common use: To show which groups of data are highest or most common, and how other groups compare against the others.

  • Drawback: Labeling and clarity can become problematic when there are too many categories included. They can also be too simple for more complex data sets.

• Histogram: A type of graph that shows the frequency distribution of data points across a continuous range of numerical values.

  • Common use: Histograms are useful for showing the frequency of a particular occurrence.

  • Drawback: The visualization can be influenced by the choice and number of categories, which can affect the shape and clarity of the distribution.

• Scatter plot: A graph that uses dots to represent values for two different numeric variables. The position of each dot on the horizontal and vertical axis indicates values for an individual data point.

  • Common use: Scatter plots are used to observe relationships between variables.

  • Drawback: If you use a too tall or too wide aspect ratio for your graph, you might exaggerate or minimize the strength of the relationship.

• Line graph: A graph that utilizes points and lines to represent change over time.

  • Common use: They are usually used to display continuous data and are often used to show changing information.

  • Drawback: If you plot too many lines on the same graph, it can become cluttered and hard to read.
    
    

Now, let’s recap the charts that we learned:

• Pie chart: A pie chart is a type of graph representing data in a circular form, with each slice of the circle representing a fraction or proportionate part of the whole.

  • Common use: This is used to show the proportion of data points belonging to a particular category against the whole.

  • Drawback: It can be difficult to compare the exact values or proportions of the categories, as the human eye is not very good at judging angles and areas.

• Gantt chart: This chart illustrates work completed over a period of time in relation to the time planned for the work.

  • Common use: These charts are commonly used to plan and track tasks within a certain project.

  • Drawback: They can easily become overly complex and they need constant updating.

• Timeline: A graphical representation of a period of time, on which important events are marked.

  • Common use: To give an overview of events or depict different temporal relations.

  • Drawbacks: Timelines don’t always give the full story or provide detailed information about each plot mark.

Let’s review the one type of diagram from this lesson:

• Venn diagram: It uses overlapping circles or other shapes to illustrate the logical relationships between two or more sets of items.

  • Common use: These diagrams are commonly used to compare and contrast the characteristics of different data sets.

  • Drawback: They can become overly complex and difficult to interpret when dealing with more than three sets.

Now, let’s recap the maps and matrices that we learned:

• Heat map: A representation of data in the form of a map or diagram in which data values are represented as colors.

  • Common use: In business, they’re used to give a visual representation about a company's current functioning, performance, and the need for improvements.

  • Drawback: These maps can be easy to misread.

• Choropleth maps: A thematic map that is used to represent statistical data using the color mapping symbology technique.

  • Common use: These charts are commonly used to compare relative data and highlight their differences across geographic locations.

  • Drawback: In choropleth maps, the areas are not uniform, often with big size differences among the areas. This can create misinterpretation if the larger areas are given more importance simply because they are larger and have greater visual impact.

• Mind map: A brainstorming technique used to visually organize information into a hierarchy.

  • Common use: These maps are commonly used for summaries, brainstorming and ideation, problem solving, content creation, and taking notes.

  • Drawbacks: Mind maps can be time-consuming to create, especially if you have a lot of ideas to organize.

• Word cloud: A collection, or cluster, of words depicted in different sizes. The bigger and bolder the word appears, the more often it's mentioned within a given text and the more important it is.

  • Common use: To get insight into the most popular concepts or to reveal sentiment. It provides instant analysis and visualization of word data and feedback.

  • Drawbacks: Word clouds only show how often words are used and do not show how words are used or what words relate to each other.

Check out our data visualization resource for more information on how to represent different types of data.

Let’s look at some additional tips to make your data visualization more interesting, dynamic, relevant, and well-received by diverse audiences.

• Use predictable patterns for layouts: Our eyes are drawn to indicators that tell us important information at a glance. We naturally seek patterns, and if patterns are random or don’t make sense, it’s very difficult to understand what the visualization conveys. To capitalize on these human tendencies, make sure the order or format in which you present data makes sense to viewers; whether it’s numeric, alphabetical, or sequential.

  • Example: If you are communicating in a language that reads left to right, then orient your visualization to adhere to that convention.

• Help tell your story with color: Use color to highlight and accentuate the information. Too many colors will create a cacophony, while using a single color or too many shades of one color can cause the data to blend. Color association matters, too. Use intuitive colors that make sense to the viewer so they process the information faster.

  • Example: If you’re working with temperatures, use red to indicate heat and blue for cold.

• Avoid too many dimensions: There’s something very appealing about fancy 3D charts. However, in most cases, the third dimension — or depth — is purely decorative, and makes it difficult for people to process the data. Unless you’re actually plotting the third dimension, don’t use 3D graphics. It can skew data and make comparisons harder.

  • Example: In a 3D chart, the back part looks smaller in relation to the front, or is even hidden by it, which makes judgments of values and comparisons almost impossible.

• Apply text carefully and intentionally: Your choice of text can improve your visualization, whether it’s the kind of text you use or even how much. While text is distracting when there’s too much or if it’s not organized in a visually pleasant way, sometimes relying only on visuals doesn’t suffice.

  • Example: Place the most important view at the top, or in the upper left corner. Your eye is usually drawn to that area first.

When it comes to structuring your presentation and building a persuasive narrative, there are several key elements to consider. First, it's important to grab your audience's attention right from the start. You can achieve this by opening with:

• An intriguing rhetorical question

• A surprising fact or statistic

• A relevant quotation

• An interesting anecdote

• An evocative image or description

• A common misconception

Empathy in storytelling captures the spectrum of human experiences, representing diverse perspectives and cultures. It invites audiences to step into different characters' shoes, fostering understanding and compassion. It creates:

• Emotional engagement: Empathy makes audiences care about what happens to the characters, making them more invested in the story.

• Narrative depth: Empathy allows for a deeper exploration of complex emotions and themes, enhancing the impact of your story.

• Audience connection: Empathy forms a bridge between the story and the audience, making them feel seen and understood. This, in turn, causes them to be more likely to take action as a result.

Slideshows are a great tool to support your presentations. Let’s go over some of the benefits of slideshows:

• Visual Appeal: Slideshows allows users to create visually appealing presentations with a wide variety of design templates, themes, and multimedia elements. The ability to add images, charts, graphs, videos, and animations makes it easier to illustrate complex ideas and captivate the audience's attention.

• Organization and Structure: Slideshows provide a structured framework for organizing information. The use of slides, bullet points, headings, and subheadings helps presenters outline their content in a logical and organized manner. This structure can enhance the clarity and comprehension of the material being presented.

• Flexibility: Slideshows offer flexibility in terms of customization and adaptability. Users can choose from a wide range of layout options, fonts, colors, and transitions to tailor their presentations to suit their specific needs. Additionally, presenters can easily modify and update slides as new information becomes available.

• Audience Engagement: Slideshows enable presenters to engage their audience through interactive elements such as quizzes, polls, and hyperlinks. These features encourage participation and interactivity, making presentations more dynamic and memorable.

Now, let’s understand some of the disadvantages of using slideshows for presentations:

• Over-reliance on Slides: Some presenters may become overly dependent on the software and rely heavily on the slides to convey information. This can result in a monotonous presentation style and a lack of personal connection with the audience.

• Information Overload: While slideshows allow for the inclusion of multimedia and other visual elements, it is essential to strike a balance. Excessive use of graphics, animations, and transitions can overwhelm the audience and distract from the main message. Presenters should be cautious not to overload their slides with unnecessary information.

• Lack of Adaptability: Slideshow presentations are often linear and follow a predefined sequence of slides. This lack of flexibility may limit the presenter's ability to address specific questions or digress from the set structure. It can also make it challenging to accommodate individual audience needs or adapt to unexpected changes during the presentation.

Take a look at our Inclusive AI Usage course for tips on how to use AI to build presentations.