Data Visualization and Interactive Graphics
We are all used to looking at spreadsheet-style tabular reports from databases. The process of sorting, filtering, moving columns, and wading through lists is time consuming and filled with trial-and-error guesses about the data.
To modify an old expression, a picture is worth a thousand spreadsheet data cells. Data visualization and interactive graphics enable you to instinctively see previously hidden patterns. You can make faster and better decisions. Here are some of the things that are easier to see interactively and graphically:
- Data trends
- Relationships and relative sizes in data
- Places to drill down, with interactive ways to reach specific detail
- Data which are special, similar, or unusual
- Exceptions, outliers, and data entry errors
Finding the Needle
When first faced with a spreadsheet containing large amounts of data, the hardest thing is often just to find the relevant data. For example, if you had a database containing information on thousands of medical studies, how would you find just the ones you need? The spreadsheet view on the top of the example shows what you might be dealing with. If you wanted to find the reports that contained information on elderly patients with at least 100 patients, you would need to sort and filter the results.
Below the table is a graphical representation of the same data. The studies on the elderly are represented by the dark blue circles. It is easy to pick them out. And, any dark blue circle that is above the 100 line is our populations. If this was a real working program instead of an illustration, you could click on one or more circles to open the reports.
For a Demo of Data Visualization with Interactive Graphics, please see our:
Interactive Dashboard Demo
Coordinated Graphs To Spot Trends
Placing more than one graph next to each other can make it easy to spot trends and to compare different items.
The chart on the left shows the number of students who have selected each major of study at a college or university over time. By looking at each line, it is easy to see which majors are growing in popularity and, therefore, may require more resources.
The more complicated chart on the right contains “sparklines” that provide more detailed comparisons. This particular set of sparklines shows important statistics for pages on a web site. By placing the information in rows, a trellis of information is created. It makes it easy to spot overall trends for the web site as well as specific trends for each individual page.
Finding Outliers and Correcting Errors
One of the unsung, but valuable, uses for data visualization is to find outliers and potential data entry errors. Graphs make them easy to spot. The graph on the left shows several unusual data points. For example, there are a cluster of three data points on the top left of the screen that do not follow the general trend of the data and are by themselves.
If this was a real analysis, clicking on the data points would open the record behind the information so that you can see why these points are different. You may find that these data points are critical findings, such as exceptions that could cause a life threatening situation. Or, they could be the data points that unveil a new major finding that leads to success.
On the right are pie charts showing another aspect of the same data. But, looking at the legend quickly shows that there are some errors in the data. For example, “Hospital (Inpatient)” appears to have two entries. It is likely that one of the two entries contains an extra space. This type of coding error could throw off a typical analysis. But, the problem is easy to spot using a legend in a chart.
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