The Joy of Data Viz: The Data You Weren’t Looking For

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Data visualization can help find patterns in data, sometimes leading to unexpected results.

“A good sketch is better than a long speech” – Napoléon Bonaparte

I recently came across this quote on the opening page of Phil Simons’ book, “The Visual Organization, Data Visualization, Big Data, and the Quest for Better Decisions.” It is available online.

Data visualization, or Data Viz as it is often referred to, is expanding – especially in the area of analytics. Numbers are numbers – but if you can represent it graphically, it enters the realm of meaning. If we represent the data visually to a detailed level of grain, it can bring about surprising discoveries.

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Data visualization can bring what was once hidden into plain site. In Zen terms, it can help one achieve what is called “beginner's eyes.”

I talked to Yasmeen Ahmad, a talented and creative data scientist at Teradata, about her visualization project titled “Trapping Anomalies.” In this visualization, the two unexpected blue clusters helped to identify fraudulent behavior.

To see the full visualization and details about the project, visit the Teradata Art Gallery.


For this visualization, Yasmeen used an open source tool called Gephi. The tool called Gephi bills itself as “The Open Graph Viz Platform.” This is a great interactive tool for data analysis. It can use just about any data source you provide. To download the tool, click here.

There is so much to explore – and so I thought I'd help you find even more to check out for yourself. Here are some other open source data visualization tools that are widely used.

D3 – a library: D3 stands for data-driven documents. It is a JavaScript library for manipulating documents based on data. You can go to download the latest version by visiting this online page. And here is an example of a tree structure that is created with D3.

R – a language: R is a language and environment for statistical computing and graphics. It provides a variety of statistical and graphical techniques, and is highly extensible.

Processing: Processing is a programming language used within the context of the visual arts. Even with some very basic code and your data source you can create stunning visuals. Here is an example of a visualization I did a few years ago using just the color data from an image of the Golden Gate Bridge.

 The Joy of Data Viz: The Data You Weren’t Looking For

The image on the left is the source for color data and the image on the right is the visualization at a point in time – as the code continuously scans the colors.

To visit the site and download the processing code, click here.

Also, here is a link to an interesting video by Jer Thorp, my former instructor. The guy is brilliant. His work brings to light some interesting “data made human” ideas – which I find very intriguing – and inspiring.

There are also several “data viz" products on the market today. While Tableau is one widely known tool, the Teradata Aster Discovery Platform provides a suite of ready to use SQL for data discovery and visualization. Here is a link to the Aster visualization presentation .

These are exciting times for data visualization techniques and related tools. I hope this quick overview gives readers some ideas for further exploration into the world of Data Visualization. There are so many positive surprises to be discovered in the data you weren't looking for!

This article was originally posted at It has been reprinted here with permission. Teradata retains all copyrights.


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