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Why is Color so important in data visualization?

by Hrvoje Smolic, Owner/Partner, Qualia d.o.o.Tuesday, October 1, 2013

The point of Data Visualization

Many business intelligence tools available today are failing to deliver actual intelligence. IT has made a great technical progress in data integration, cleansing of transformation as well as in construction of big and efficient data warehouses. Nonetheless, we think that business intelligence industry has largely ignored the fact that actual intelligence is within human beings. Therefore, raw information can only be valuable when it is understood and not just when it is available.

If data is poorly represented, whole great data warehouse project was in vain.

Mission of BusinessQ

We want our Business Intelligence and data visualization software to leverage the strengths of human perception in general. Very important part of that perception are our eyes (70% of receptors in our body are in eyes!). Color can be used as a very powerful way to enhance the meaning and clarity of quantitative data, but also can add problems if it’s used improperly. That is why in BusinessQ we made several color palettes – we simply don’t want to allow report designers to make nonfunctional reports.

Our BusinessQ default color palette has soft, natural colors on left side and bright and dark colors on right side:

The purpose of soft colors is to present the most of information:

On the other hand, if we want to highlight some information and we want to draw attention to particular data, we will use right-side spectrum of our palette: (notice how red color is much brighter then other two measures):

Usage of soft pastels can fail to correctly present data if you are using scatter plot, because of small or thin objects:

Compare that screenshot with second one and decide which is more readable:

Our default palette is made in such a way, that if you follow on row from left to the right, you will get sequential colors that will surely be distinct in any graph.

Moreover, we know that some people cannot distinguish particular colors that most people distinguish quite easily. Approximately 10% of males and 1% of females suffer from abnormal color perception commonly known as colorblindness, which is a fairly big percentage (especially for men). Our palette – if followed from left to right – will ensure that even those people will be able to read any BusinessQ graph.

Predefined BusinessQ Palettes

As mentioned at the beginning, we also made several predefined color palettes to ensure that you don’t have to worry about colors – because we have.

Among them there are

  • qualitative palettes – the ones that are used to separate items into distinct groups – hues are used to create the visual differences between items. Qualitative palettes are best suited to represent nominal or categorical data.
  • Sequential and diverging palettes – primarily used to encode quantitative differences Here is one the same chart in some of our predefined palettes:

BusinessQ default palette:

Soft Pastels:



Originally posted on Qualia

About the author

Hrvoje Smolić is the Owner and Managing Director at Qualia d.o.o. He is responsible for all parts of the planning and development strategies, as well as for continually improving processes to fulfill the mission. As Creative Director he develops and oversees the overall look of applications, using design principles to organize their content and ensure full user-application communication. He defines their structure, information design and interface.
Before founding Qualia, Hrvoje had seven years of experience in the IT community. He began his career developing commercial applications for the banks, with client-server programming and relational database modeling in the role of business analyst in the company Vestigo. Later, as employee at Adacta he started as a consultant for Business Intelligence (BI), and then moved to position as Head of BI and CRM team, BI project manager and as a product manager. He has a degree in Physics from Zagreb University and is currently on PhD.

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