Power of Data Visualization and Charts

Data visualization

Numerous researches in the field of cognitive neuroscience show that your brain loves a visual content more than plain text.

This fact is not surprising at all – the reason for the better perception of visuals is deeply rooted in our first language that consisted of pictures on cave walls. We are biologically wired to perceive information visually.

But let’s get back to nowadays. As an analyst, you can take advantage of that natural aptitude by mastering visualization techniques and tell better stories that are based on the data analysis. For sure, one of the visual tools you should make use of is a presentation.

It can be composed of multiple elements but the best way to make it effective is by using charts, graphs, and diagrams. So, today we’re going to sort out what charts are, why and how to use them appropriately to enhance the perception of information.

It is the first contribution to our data visualization project, which covers a lot of visualization techniques and best modern approaches.

So, let’s start with the theoretical concepts. A bit of theory never hurt anyone 🙂

What is a chart

To put it simply, a chart is just a graphical depiction of data expressed in various symbols (bars, lines, slices, etc). The term ‘chart’ is often used interchangeably with the terms ‘graph’ and ‘diagram’.

Why use

The main purpose of charts is to make the meaning of analysis results as easy-to-comprehend as possible. Use them to convey a certain kind of relationships between dependent and independent variables, comparing values or capturing trends.

A bit of history

Most of the charts you know were introduced at the end of the 18th century by William Playfair. With the passage of time, they have undergone some visual changes and found new applications not only in the sphere of economics but in various industries that are managed by data-driven processes.

Charts types

Charts can be depicted as two-dimensional or three-dimensional. Among all, 2D charts are used most often because they are readable and easy-to-understand.

If you have three- or multidimensional data, you can still represent it in a two-dimensional space. For example, by adding the color or the size of the data points as an additional variable. There are many charts that allow such a trick (a vivid example is a bubble chart).

However, it is much more interesting to divide charts according to their purpose. In the following articles, we’ll find out what categories of charts exist and in what situations it’s better to use them. We don’t set ourselves a goal to list all the charts but we’ll take a look at their most prominent representatives.

Choose charts wisely

The first thing every analyst should care about is making sure the data fits the chosen chart. Some types are suitable for qualitative data (e.g., product’s color and category) while others – for quantitative (e.g., product’s price and shipping cost). Also, you should answer a few questions beforehand: How many variables do you need to show in a chart? How the variables should be displayed – over time or across the categories? All your answers directly affect the choice of the chart.

No less importantly, the presentation with charts should be well-designed. Otherwise, the results of data visualization may be misinterpreted by the audience. To not let that happen, we’d like to give some useful recommendations.

The golden rules for using the charts in your presentation effectively

• Readability. The first and foremost requirement – charts should be as accurate as to illustrate the trend in a truthful way without distorting facts
• Choose one style and stick to it. Don’t mix too many fonts and colors
• Use a harmonious palette that complements your data and reveals the meaning behind the analysis. At the same time, consider that some people may be colorblind and pick a scheme in favor of saturated colors.
• Use legends for charts to explain what the color scheme means
• Use high contrast between visual information and background to focus attention on the content itself
• Don’t forget about labels on charts (especially when there’s no possibility to use tooltips)
• Highlight important numbers on charts and graphs with conditional formatting
• Frame your message and give a context by adding titles and descriptions: don’t make your audience guess what
  you’re comparing and what is the purpose of the analysis.

All in all, your presentation, supplemented with charts, should be concise and easy-to-comprehend. Your audience should be able to grasp the idea you’re trying to express in a short period of time.

What’s next?

Dive into the world of charts with WebDataRocks:

• Best Charts to Show Discrete Data
• Charts for Comparison Over Time
• How to Choose Charts to Show Data Composition
• Best Charts to Show Correlation
• Best Charts to Show Data Distribution