CXL Course Review: Data Presentation and Visualization

CXL Course Review of Data Presentation and Visualization

This article is covering my 12th week of studying at CXL Institute. In the previous post I have covered presenting data using Digital Analytics Minidegree, and this week will be covering the Data Presentation and Visualization, in this course you will learn how to present data to change minds and facilitate action.

Instructor Tim Wilson is a Senior Director of Analytics at Search Discover in Columbus. He has a great knowledge on data presentation and visualisation. He clearly explained how we can build a better presentation using available resources. Thanks to Tim!

What is Data Presentation and Visualization?

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A presentation conveys information from a speaker to an audience. Presentations are typically demonstrations, introduction, lecture, or speech meant to inform, persuade, inspire, motivate, build goodwill, or present a new idea/product

Visualization, as the word suggests is the art of representing information in visual form like diagrams, charts or images. The visuals are usually supported by narration from the presenter.

This Course has 3 Parts:

1. Communication Overview:

Why analytics communication is critical when it comes to driving results using data. The below listed 3 lessons are covered under communication overview.

  • Communication overview
  • Overview: The brain science of communication
  • Overview: The Cognitive Load of Pie Charts

2. Data Visualization:

The many ins and outs of effectively visualizing data: strategies for driving readability and comprehension. The below listed 13 lessons are covered under Data visualization part.

  • Data Visualization: Maximizing the Data-Pixel Ratio
  • Data Visualization: Using Color Sparingly
  • Data Visualization: The Importance of the Axes
  • Data Visualization: Horizontal Bar Charts for Comparing Categories
  • Data Visualization: Line Charts for Visualizing Time-Series
  • Data Visualization: Sparklines and Small Multiples
  • Data Visualization: Text as a visualization
  • Data Visualization: Heatmaps
  • Data Visualization: Scatterplots
  • Data Visualization: Specialty Charts and Chart Elements
  • Data Visualization: Cautionary Charts and Bad Practices
  • Data Visualization: Dashboard Considerations
  • Data Visualization: Data Visualization Resources

3. Data Storytelling & Presenting:

Why & how to construct a narrative to ensure the information is understood, retained, and acted upon. . The below listed 10 lessons are covered under Data Storytelling & Presenting.

  • Data Storytelling: The Power of Narrative
  • Data Storytelling: Know Your Audience, Know Your Goal.
  • Data Storytelling: Establishing a Narrative (and a Flow)
  • Data Storytelling: McKinsey Titles and Reinforcing Content
  • Data Storytelling: Data Visualization Tips Apply!
  • Data Storytelling: Kill the Bullets and Limit the Text
  • Data Storytelling: Presentations vs. Documents
  • Data Storytelling: Compelling Imagery
  • Data Storytelling: Editing and Rehearsal
  • Data Storytelling: Review and Resources for Learning More

Using Color

When used correctly, color can help audience members sort out the various elements of a slide. But its power goes beyond mere clarification. To some extent the colors you choose for your visuals guide the emotional response of your audience.

Data Pixel Ratio

The Data-Pixel Ratio originally stems from Edward Tufte’s “Data-Ink Ratio”, later renamed the “Data-Pixel Ratio” by Stephen Few. The more complicated explanation (with an equation, GAH!) is:

A simpler way of thinking of it: Your pixels (or ink) should be used for data display, and not for fluff or decoration. (I like to explain that I’m just really stingy with printer ink—so, I don’t want to print a ton of wasted decorations.)

Importance of Axis

Charts are important for various reasons:

  1. Charts convey information is a way that is not propositional, that is, charts are visual. This is an important point, because some people are visual learners.
  2. Charts also break up monotony for people who are more propositional learners. This might help if the presentation is long.
  3. Charts also convey lots of information in an easy format. This alone is worth it!
  4. Finally, charts can plot various variables on an x and y plane for comparison purposes. In short, one can analyze data effectively this way.

Graphs have two axes, the lines that run across the bottom and up the side. The line along the bottom is called the horizontal or x-axis, and the line up the side is called the vertical or y-axis.

  • The x-axis may contain categories or numbers. You read it from the bottom left of the graph.
  • The y-axis usually contains numbers, again starting from the bottom left of the graph.

The numbers on the y-axis generally, but not always, start at 0 in the bottom left of the graph, and move upwards. Usually the axes of a graph are labeled to indicate the type of data they show.

Building Charts

Chart is a graphical representation of data. Data Studio provides a number of chart types, such as time series, bar chart, pie chart, etc. charts derive their data from a data source. Charts display one or more axes of information (dimensions) and the actual values contained by those dimensions or metrics.

To create charts that clarify and provide the right canvas for analysis, you should first understand the reasons why you might need a chart. In this post, I’ll cover five questions to ask yourself when choosing a chart for your data.

Types of Charts

  • Column Chart
  • Bar Graph
  • Line Graph
  • Dual Axis Chart
  • Area Chart
  • Stacked Bar Graph
  • Mekko Chart
  • Pie Chart
  • Scatter Plot Chart
  • Bubble Chart
  • Waterfall Chart
  • Funnel Chart
  • Bullet Chart
  • Heat Map

Remember These before Choose Chart Type

  1. Do you want to compare values?
  2. Do you want to show the composition of something?
  3. Do you want to understand the distribution of your data?
  4. Are you interested in analyzing trends in your data set?
  5. Do you want to better understand the relationship between value sets?

Dashboard Considerations

There Are Two Fundamentally Different Dashboard Types.

  1. Analytical Interfaces

Jumping off point for deeper analysis The user is acting “as an analyst” regardless of primary organizational role Typically violate pure data visualization “best practices”

  1. Performance Measurement

Focus is on KPIs Intended to provide an at-a-glance view of an area of the business Includes limited context and diagnostic information

The Power of Narrative in Data Story Telling

The narrative is the heart of any good presentation; without a clear narrative, there is no story for your audience to understand and latch onto. This means your audience will have to work hard to try and figure out what is being said, where you’re presentation is going, what you need them to do or think and why you are the right partner for them. It makes it hard for them to recall your key messages and retell your story to other decision-makers.

Remember: a presentation is all about getting your audience to take the action you need them to take – such as adopting an idea, moving to the next stage of their buying process etc. – therefore you must have a clear narrative argument that lays down why they should do what you want them to do. This is central to the whole idea of narrative.



I am Isak, founder and author of blog. A best place to have article through guest posts. I love reading (learning), sharing my skills and knowledge with all over the world using modern digital platforms.