Amazon Quicksight Launches Multi-Sheet Dashboards, New Visual Types and More
Released on June 12th, 2019
Amazon QuickSight announced the launch of sheets within dashboards. Sheets allow better organization of information within the dashboard, where visuals related to specific subject areas or topics can be organized in separate sheets and distinctly identified through the tab name. As a reader, you can then navigate to a single dashboard to get a comprehensive view of all the insights related to a topic. For more information, see here.
In addition to this, QuickSight launches two new visual types – Gauge and Donut charts. Gauge charts are useful when you want to display a single value within a given scale, and are a great way to show performance for key metrics towards goals. Donut charts are useful when you want to display proportion or parts to a whole, similar to a pie chart but with aggregate measures within.
You can also now apply standard deviation and variance on your data sets to derive further statistical insights from your data. Additionally, you can use conditional functions on strings (eg. ifelse) on SPICE data sets. The enhancements to the Datediff calculation now allow you to compute the difference between two date fields at the following granularities - Year, Quarter, Month, Week, Day, Hour, Minute, Second. For more information, see here.
Other improvements allow you to angle axis labels within charts to view labels clearly and duplicate visuals within the same sheet or across sheets within the same analysis. You can now hide table columns before publishing a dashboard to your users. With the enhancements on custom URL, you can choose how URLs are opened, with options of overriding the viewer’s QuickSight browser tab, loading in a new tab, or a new browser window altogether. See all new features here.
All these features are now available in Enterprise Edition and Standard Editions in all QuickSight regions - US East (N. Virginia and Ohio), US West (Oregon), EU (Ireland), and Asia Pacific (Singapore, Sydney and Tokyo).