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The 15 Principles of Data Visualization
“Having all the information in the world at our fingertips doesn’t make it easier to communicate: it makes it harder,” says Cole Nussbaumer Knaflic, a data storytelling author. She’s right. The data issue we have today isn’t a lack of it, it is the opposite — how to use the enormous amount of data being captured.
At its core, data visualization is a tool used to transform data into actionable intelligence that tells a story about a company’s data. It can be data about a digital marketing customer journey, production line data that captures product flaws, supply chain operational data that tracks products from creation to final sale, price optimization data that helps a hotel sell its rooms at the highest possible price, or data used in a thousand other business ways.
Lately, the options for data visualization software has grown exponentially. Products from commercial software companies like Qlik, Tableau, PowerBI, Spotfire, IBM, and SAP compete with powerful open-source applications, like Gephi, RAWGraphs, Plotly, and Datawrapper.
Open-source options can be tempting to use, but they can be time consuming to implement. Working with a publicly traded company whose very existence requires it to constantly upgrade its products to keep it on the cutting edge of technology is often worth the yearly product maintenance cost. However, for price conscious companies, there are a lot of open-source tools now available and the ones that have been around for a while have large developer communities built up around them filled with people who understand the product inside-and-out. Finding skilled developers for some of these open-source tools isn’t as hard as it used to be.
By asking what kind of story you want to tell with your data and what message you want to convey to your audience, business intelligence (BI) designers can choose the right data visualization tools for their data visualization initiatives.
Understanding the ultimate audience for the dashboard will help designers choose the right data visualization type for that audience. Designers should always put themselves in the user’s shoes…
