At Polychart we are passionate about visualizing data. This blog features product news, articles, as well as our own analyses and visualizations of datasets we find interesting.

Monday, 8 October 2012

The Data Visualizers

Last week MaRS Commons published an excellent showcase of data visualization startups in Ontario, Canada. The showcase includes an interview with me on behalf of Polychart. Here is an excerpt from the intro of the piece.
The creation and capture of data by itself does not, obviously, benefit anyone―only when analysis is added to the mix is the value of big data unlocked. Unfortunately, this is also an area where significant challenges exist. Big data analysis remains a market in its infancy. As Google’s Chief Economist Hal Varian put it, “Data are widely available; what is scarce is the ability to extract from them.”
No doubt, all eight startups showcased want to help people better understand data. The variety of the startups is as much a surprise to me as the amount of them. It's a pleasant surprise to find so many startups in this exciting space, so close to where we are!

Some startups are looking at better visualizing data from a single domain: Sciencescape visualizes published research data, Quinzee visualizes energy consumption data, and Infonaut and Bio.Diaspora visualize health data. Others are building tools to make understanding data and communicating results easier: Venngage is making an infographics builder, Buzzdata is making data sharing easier, DataAppeal is focusing on geo data, and of course Polychart is focused on charts (which people sometimes call "statistical graphics").

During the interview Neha asked me some pretty interesting questions about Polychart. We discussed everything from the talent gap in the field of data science, the need for more accessible ways of interacting with data, and the importance of understanding human perception in data visualization. Here are some of the questions she asked:
Why Polychart rather than a more traditional tool like MS Excel? 
The best thing about Polychart is the speed at which you can create a chart. I think iterability is extremely important when you’re analyzing data, since you tend to think of ideas as you’re working. If there’s a lot of friction between when you thought of an idea and when it shows up on the screen, then that idea just gets lost. In data analysis, this can mean the difference between having a key business insight and not. 
Visualizations can often lead to different interpretations, simply by the way in which the data is displayed. Does Polychart address this challenge? 
This is one thing we take very seriously. There is ample research into the field of perception that tells us what our visual system pays attention to. For example, people are very good at comparing areas, and so it’s helpful to start the y-axis of a bar chart at zero. It’s also why 3D effects on bar charts and pie charts can distort the data being displayed. 3D effects do a great job at grabbing someone’s attention, but when doing data analysis, accuracy is much more important.
You can read the full interview here.

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