How to Nail the Basics of Data Representation

Knowing data analysis is great.

Knowing visualization is great.

But how do you know when you’ve mastered both?

It's easy to find out. You're on point when your boss and client look at your slide and draw the same immediate conclusion.

Great, but how do you go about it? 

Some people think data visualization is about showing off the complexity involved in analyzing large datasets, or demonstrating how advanced your analysis is. It is quite the opposite.

In our experience, the true test of skill is making complicated matters simple.

Here's how you can apply two factors that will guarantee to help you produce professional and persuasive slides:

1) Simplify the data and make it easy to draw conclusions

2) Focus on one takeaway

1) Simplify the data and make it easy to draw conclusions

Your aim, with any presentation, should be to save the audience’s time and help them make the right decisions. You want to reinforce the right data, draw their eye to the right section of the page, and do every bit of the analysis for them without creating a bias.

Take something so fundamental as a bar column or chart. It's useful when comparing one to three variables across categories. Look at the two charts below vary in their simplicity and their ability to convey one message. 


What’s the bottom line?

The pink highlight shows that companies are in focus and it supports the heading of the slide, leaving the audience to draw only one conclusion: Only two companies are among the ten most popular Facebook pages in Denmark. The data labels placed on the 'outside end' also aid the audience to understand the data instead of trying to use the y-axis to interpret the data. It requires less effort to look at the numeric value than to guesstimate based on an imaginary horizontal line.


You have a simple chart that is easy to interpret, time give your takeaway center stage.

2) Focus on only one takeaway 

In the first example, there is no takeaway. Only a list of data points the audience must digest on their own. This leaves room for confusion and thus requires interpretation.

What if their minds wander off, or what if they arrive at a different conclusion? Maybe they think it's crazy that Benjamin Lasnier has more followers than Martin Jensen, or maybe they start to wonder who these people even are. Even worse, they might Google it under the table, and you have now managed to lose their attention completely.

But not to worry, the second example provides clarity and focus.  

In the second example, you steer them to focus on the companies, and you establish a common point of reference. A situation that both parties agree to, and from here, you can talk on equal terms about what you want to do about the situation.

What’s the bottom line?

Decision makers are busy and eager to discuss conclusions and actions rather than method and academics. In general, they'll lose interest in your analysis if your slides don’t exemplify your point. This is why it is important to present your data uncomplicated, without room for misinterpretation.

In our free ebook on data visualization, we cover both how and when to use the fundamentals and advanced data visualization – all the way from basic pie charts to advanced think-cell and Pareto charts.

So… what are you waiting on?

It's free, takes less than 7 minutes to read, and most importantly, it will make your slides look more professional and easy to understand.

Click here to start learning.

In case you would like a little sample before you download the full thing, we have provided a teaser below where you can read more about the basics.   

The Line Graph

Line graphs are a great way to show how data changes over time, especially if you have more than 10 data points. The continuous line makes it easy to show volatility, stagnation or trends. As a default, NoMore does not use gridlines because we show the numbers. However, for line charts, one might consider including gridlines if a specific number is of high importance.

When to use: you want to illustrate changes in data over time and have many data points.

Scatter Plot

Scatter plots show the correlation between two variables; they can be used to see if data follows a pattern and show a relationship. For example, you might assume that people who put in more hours at work are -on average - likely to receive higher bonuses. A scatter plot can show how strong that correlation is –or isn’t.

When to use: you want to show correlation between two quantitative variables,

Bar chart

Bar charts are best used to compare 1 -3 quantitative variables across categories –companies, time, etc. As a rule of thumb, you should only use a bar graph if you have 10 data points or less. If you have more than 10 data points, consider using a line graph instead.

When to use: you want to compare one to three variables across categories. It is also possible to add qualitative variables.

Want to read the whole thing? Click here to download our free ebook.

Rune Johansen
Published by Rune Johansen

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