Seven steps to visual data exploration
With visual analytics, anyone can explore data to uncover hidden trends and new opportunities
Imagine that you’re a business analyst for a manufacturing company, and you want to understand revenue expenses. What if you could simply drag and drop hierarchies or categories onto a visualization pane and see instantly how revenue expenses were trending across the company? And what if, by hovering over the bubbles on the chart, you could see which regions were performing better than others and by how much? And what if double-clicking on a bubble would give you more details about that region? With SAS® Visual Analytics, it's as simple as that.
"One of the first things a business analyst wants to do when presented with a new set of data is to get some idea what it's about," says Jim Goodnight, CEO of SAS. "What are the outliers? What variables are related to each other? Up until now, analysts had to spend hours and hours doing samples so they could actually get jobs to run. With SAS Visual Analytics, you can cruise all your records to create graphs and plots one after the other. It really allows you to understand your data better."
7 steps to fast, easy data exploration:
ONE: Create your own hierarchies
If you need the data organized a certain way for the business problem at hand, you don't have to seek help from IT. With SAS Visual Analytics, you have access to all of the data and can create and modify your own hierarchies to explore it, however and whenever you want.
First, you simply create a new visualization. Then within the "Create a new hierarchy" area of the software, you can double-click or drag and drop the items (from a menu selection box) where you want to build a hierarchy. To view how the new hierarchy appears in the visualization, you can double-click on a bar in a bar chart or on a slice of a pie chart, and then drill down to different levels or go back up a level, depending on what you need. All of this can be done in seconds.
TWO: Choose the best visualization for the data
Since determining what type of chart to use can be a challenge, SAS Visual Analytics uses intelligent autocharting to recommend the best visual for the information. For example, if the data has geographic elements, SAS Visual Analytics may propose a bubble plot superimposed on a map of the regions. Or it may choose a line chart as the best visual for a selection of two variables, then change to a clustered bar chart when a third variable is added. Or, you can select the visual you want.
Fig. 1. Click to enlarge
THREE: Understand the distribution of the data
Understanding the distribution of the data is as simple as creating a new visual and dragging the measure or category onto the visualization pane.
By default, SAS Visual Analytics automatically calculates the best distribution for the data. But you also have the option to change that visual. Take an example of a very large data set. If you wish to view the distribution of all the data points in the data set, a histogram will help – but another visual that might help you more quickly understand how your data is grouped is a decision tree (see Figure 1).
FOUR: Identify relationships among variables
Simply select a group of variables and drop them into the visualization pane, and the intelligent autocharting function will display a color-coded correlation matrix that quickly identifies strong and weak relationships between the variables. Darker-colored boxes indicate a stronger correlation, lighter boxes a weaker correlation. You can hover over a box to see a summary of the relationship. Or double-click on a box in the matrix for additional detail
Fig 2. Click to enlarge
FIVE: Look to the future: forecasting at your fingertips
SAS Visual Analytics takes the complexity out of forecasting (see Fig. 2), so all types of users can see for themselves what might happen in the future. You no longer have to select the best forecasting algorithm for your data, since the software generates forecasts dynamically by automatically selecting the most appropriate algorithm. You can forecast with confidence: SAS Visual Analytics automatically shows you the confidence intervals associated with your forecast. You also have the option to select the forecasting intervals.
SIX: Create your own visual reports and dashboards
Once you've had a chance to visualize and explore your data, you'll likely see something that you want to share. Or you might want to generate a report. The SAS Visual Analytics Designer provides the tools to create and distribute Web-based reports.
Through a graphical interface, report authors can get wizard-driven help for previewing, filtering or sampling data before creating visualizations and dynamic, interactive reports. For example, reports can have multiple tabs, each with unique sets of visualizations, all of them clickable to explore up or down a level in the hierarchy. With drag-and-drop simplicity, report authors can define the interactions among visuals in a report, specify the type and appearance of the report page, and add labels and annotation.
Fig. 3. Click to enlarge
SEVEN: Publish to the Web and mobile devices
Decision makers can quickly open, view and interact with reports from the Web, via an Adobe PDF file or from an iPad® or Android tablet (see Figure 3). Easy-to-use collaboration capabilities promote idea sharing while saving valuable time. You can annotate screen captures of reports and email them to others, who can add their thoughts as well. Or capture your comments via video and audio to share.