Vista Analytics Best Practices: Match Your Data with Your Analytic Output Type

Vista Analytics allows you to feed different variations of the same data into its grid and graph display formats. You can even specify an additional configuration for its Excel output. Why not take the extra time to consider how each output type can best express your data, making it most impactful?

As an example, let’s say that you want to make an analytic that shows the candidate sources from your recruiting efforts. And let’s further assume that you draw candidates from many sources, but the majority come from only a few. And for now, let’s finally assume that we’re not interested in prior years’ or departments’ efforts—just information about your current recruiting campaign.

Let’s start with a graphical representation. Remember from a prior article in this series, that graphs/charts are supposed to visually convey insights at a glance. So a pie chart might be a nice graph type. That way someone can easily notice which sources are the largest. But what if you had candidates coming from 20-30 different sources, even though the majority just came from a few? Then a pie chart with 4-5 larger slices along with 20+ slivers not only looks ugly – it distracts from the message. The user’s eyes naturally gravitate to the mess of the 20+ crowded slivers vs. to the more important larger slices. So for a pie chart, you might want to tweak your incoming data to only include numbers for the top 4-6 slices, and then add a data point for “All Other.” Then, at a glance you can not only convey the importance of the larger individual contributors, but you can also convey the comparative importance of all of the smaller ones in aggregate.

On the other hand, a grid display allows you to review and inspect each contributor as you need, by scrolling up and down to it (especially if sorted). But a grid display, by its very definition, allows for multiple columns. Therefore, you can provide more information for detailed review. In our example, in addition to showing the number of candidates by source, you can have columns that break down the number of candidates in other sub-categories—e.g., those considered for the next level in the review process, those to whom offers were made, etc., or broken down in other ways such as by sex, age, or years of experience.

Finally, consider the data for an Excel export. The intent of a Vista Analytic grid display is to provide enough information for more review and/or for drilling down (which we’ll review in a subsequent article)—but not so much to be overwhelming or too busy and distracting. However, if a user chooses to export to Excel, it’s because he wishes to dive into more details. So consider adding as many other columns of information that a user might find useful. (The difference between Excel and Vista grid data becomes even more pronounced when you consider detailed lists and drilling down. In a Vista analytic grid you can include just enough information to identify the entity—person, location, whatever—and let the person click on it to drill down to the details. But when exporting to Excel, you might want to include all of the detail columns that a user disconnected from Vista might need.)

This article is part of the Vista Analytics Best Practices series. If you missed our last post, click here to read about matching your graph type with your story. Or, continue to our next post on how to Simplify Your Data Access.

Marco Padovani
Senior Development Manager | PDS