How to make data visualization more intuitive with auto charting


Last year I was given an iPad. At the time I was rather ho-hum about my new toy, but my fourteen-year-old daughter was ecstatic about it. I now know why.  Today, I am writing this blog post from my iPad and I am lost when I leave it at home. The reason I am lost is because of the ease-of-use of this product.

It had been a long time since I had used software that felt like it was custom written for me.  The transparency of the tool allows you to concentrate on the important things… the rest comes easily and intuitively. That means from day one, when developing products for the iPad you can focus on the user experience, making the power of SAS analytics readily and easily available to the business analyst.

SAS Visual Analytics is a new offering from SAS that allows a business analyst to explore data, really big data, in an intuitive user experience. While exploring data is fun, the business analyst will want to share their findings with their peers and project stakeholders through flexible reporting options. I will focus today's blog entry on the user experience and discuss reporting options in a future blog post.

One key technology the SAS Visual Analytics team has leveraged for ease-of-use is auto charting. Auto charting is a technique that combines advanced data knowledge plus the science of data visualization and exploration to assist, or guide, the user to the next level of data discovery. This allows the user to see the data in ways they may not have considered; thus encouraging fresh, new discoveries they may not have otherwise encountered. This guide is especially helpful to users who are new to the world of data visualization.

Let's look at an example. If I start with a new visualization on a set of data and drag a measure, such as “revenue,” to that visualization I would be presented with a distribution of revenue and thus I get immediate feedback about the data.


If I drag a “time series” onto the visualization, I would be presented with a line chart; the best visualization for time series.

VAE Time Series

If I drag a character-based categorical variable, I will get a bar chart; again the appropriate visualization forthe data. Auto charting does not prevent the user from choosing another chart type, it just provides guidance. Now let's say I want to rank “revenue” descending. A quick click on the bar chart icon and I can quickly rank the results.

VAE Bar Chart

If your boss asked you to report on why production numbers were down for one of your manufacturing plants in Chicago, what would you do? In SAS Visual Analytics you could grab all of the measures and it will automatically generate a correlation matrix.

VAE Correlation Matrix

It does this quickly, even with billions of rows of data. Just double click on a crossing to drill into the details. Pretty cool...

VAE Heat Map

There are many other examples of auto charting you can explore. In my next blog post, I’ll share more about the reporting options in SAS Visual Analytics.

Learn more about "big data" visualization - and more - in this special 32-page report on high-performance analytics.


About Author

Don Chapman

Director, Research and Development

Don Chapman is a Director in the SAS Business Intelligence Research and Development division. His team marries the latest analytic technologies at SAS with a cutting edge user experience to make visual exploration of big data both productive and fun. During his 20 years at SAS, Don has been awarded the CEO Award of Excellence and membership on the R&D High Performance Team. Prior to joining the management team, he was a software engineer focused on user interface development.

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