Data scientists and analysts love digging into the architecture of data to grasp its essence, exploring how it works and divining what secrets it may hold. For some expert users, the very complexity of the data is what provides the "thrill of the chase." However, the average user wants data that’s easy to understand. Visualization has proven to be the best way to make this happen.
Why does visualization work so well?
Noah Iliinsky, data consultant and coauthor of Beautiful Visualization and Designing Data Visualizations, spoke at a LinkedIn Tech Talk about the reason visualization is so powerful for analytics. "It turns out that our eyes and our brains have very sophisticated software built into them for things like pattern recognition and detecting when there are pattern violations on a variety of factors in terms of position, skew, color, size, blur, shape, etc. They are called ‘pre-attentive properties’. We can detect very quickly when something is different or out of position. If you leverage these well, you can design things where you can get a lot of information into someone’s brain very easily and very quickly."
Enterprises are demanding more visualization
Business users may not know the science behind the way their brains process data, but they know what works. Presentation is king. Distilling data into the essential intelligence that will inform business decisions is pointless if the resulting reports are visually opaque. According to a recent TDWI white paper on self-service BI, "For information consumers, the results need to be easier to consume and use, and the solution here is to employ more sophisticated visualization techniques. These vary considerably, from using technologies such as Google Maps to display location-specific data, to visualization approaches such as small multiples, scatter plots, heat maps, enclosure diagrams, node links, arc diagrams, and more. Advanced visualization ranked third highest in the survey for enhanced user interface requirements, with 41% of respondents saying this was a ‘very important’ requirement."
Tools must match the source, complexity, and variety of data
Being able to look at the same data in many different ways is critical since each perspective can add depth. The data visualization tools of the past, with their two-dimensional pie and bar charts, simply aren’t refined enough to offer real insight into complex data sets. Imagine trying to track the proliferation of power stations across the United States over time using a traditional Excel spreadsheet and a set of static graphs or charts. Assuming you have the relevant information stored on your SQL server, you could sort and present the data by date of initial operation, by state, by county, by power station type, and so on.
However, making sense of the data really requires a map—and some way to visually express the changes that are taking place over time. The new "GeoFlow" visualization tool from Microsoft is a good example of how geographic data can be viewed in a way that permits the eye to easily detect patterns. It also includes the ability to drill down into the data after the overall trends become apparent so that users can uncover additional intelligence.
More features of a smart enterprise BI tool
Beyond offering many ways to present BI, the right solution will also give users more control over reporting. While visuals are important, they shouldn’t distract from the data or from business objectives. Every feature should be easy to use and fill a functional role. Here are a few key features that make a difference:
- Interactivity, especially the ability to slice and dice the data
- Full OLAP support
- Static and dynamic capabilities
- Visuals that relate to the real world within which the business operates
- Multidimensional analysis
- Collaboration for team analytics
- Real time or near real time capability for live BI needs
Meta-visualization in dashboards
Visualization is about more than individual reports designed for distinct purposes or for certain departments. Dr. Joseph Morabito, Industry Associate Professor at the Stevens Institute, maintained in his 2012 talk about Big Data that different users require different types of visualization in terms of dashboards.
"The strategic dashboard is focused on high-level measures of performance. Typically, they feature static snapshots of data on a daily, weekly, or monthly basis, and there is little user interaction. You don’t want too much here. It’s better to be simple. Analytical displays are designed for detailed data analysis. Here, you’re going to have comparatively more data (and more complex data) but richer comparisons. You’ll have extensive historical data, but still mostly periodic snapshots. You’ll have a lot of interaction here with many OLAP features. Operational data requires a dynamic environment where we are using real-time or near real-time data (as in monitoring a supply chain management system). Here we need to keep it simple, as we do with the executive dashboard, but for different reasons. We need to see problems right away and then drill on demand so we can locate problems as they arise in real time."
In the final analysis, users want more than BI solutions that enable them to achieve goals in their business. They want tools that make them feel smart. That’s the kind of positive reinforcement that provides the motivation leading to innovation. A data visualization solution that is versatile, well-rounded, and accessible for self-service is the best BI tool for this purpose.
What types of visualization techniques to you use to make BI analysis easier? Let us know.