AWS Big Data Blog
New scatter plot options in Amazon QuickSight to visualize your data
Are you looking to understand the relationships between two numerical variables? Scatter plots are a powerful visual type that allow you to identify patterns, outliers, and strength of relationships between variables. In this post, we walk you through the newly launched scatter plot features in Amazon QuickSight, which will help you take your correlation analysis to the next level.
The scatter plot is undoubtedly one of the most effective visualizations for correlation analysis, helping to identify patterns, outliers, and the strength of the relationship between two or three variables (using a bubble chart). We have improved the performance and versatility of our scatter plots, supporting five additional use cases. The following functionalities have been added in this release:
- Display unaggregated values – Previously, when there was no field placed on Color, QuickSight displayed unaggregated values, and when a field was placed on Color, the metrics would be aggregated and grouped by that dimension. Now, you can choose to plot unaggregated values even if you’re using a field on Color by using the new aggregate option called None from the field menu, in addition to aggregation options like Sum, Min, and Max. If one value is set to be aggregated, the other value will be automatically set as aggregated, and the same applies to unaggregated scenarios. Mixed aggregation scenarios are not supported, meaning that one value can’t be set as aggregated while the other is unaggregated. It’s worth noting that the unaggregated scenario (the None option) is only supported for numerical values, whereas categorical values (like dates and dimensions) will only display aggregate values such as Count and Count distinct.
- Support for an additional Label field – We’re introducing a new field well called Label alongside the existing Color field. This will allow you to color by one field and label by another, providing more flexibility in data visualization.
- Faster load time – The load time is up to six times faster, which impacts both new and existing use cases. Upon launch, you’ll notice that scatter plots render noticeably faster, especially when dealing with larger datasets.
Explore advanced scatter plot use cases
You can choose to set both X and Y values to either aggregated or unaggregated (the None option) from the X and Y axis field menus. This will define if values will be aggregated by dimensions in the Color and Label field wells or not. To get started, add the required fields and choose the appropriate aggregation based on your use case.
Unaggregated use cases
The following screenshot shows an example of unaggregated X and Y value with Color.
The following screenshot shows an example of unaggregated X and Y with Label.
The following screenshot shows an example of unaggregated X and Y with Color and Label.
Aggregated use cases
The following screenshot shows an example of X and Y aggregated by Color.
The following screenshot shows an example of X and Y aggregated by Label.
The following screenshot shows an example of X and Y aggregated by Color and Label.
In summary, our enhanced scatter plots offer users greater performance and versatility, catering to a wider range of use cases than before. The ability to display unaggregated values and support for additional label fields gives users the flexibility they need to visualize the data they want. For further details, refer to Amazon QuickSight Scatterplot. Try out the new scatter plot updates and let us know your feedback in the comments section.
About the authors
Bhupinder Chadha is a senior product manager for Amazon QuickSight focused on visualization and front end experiences. He is passionate about BI, data visualization and low-code/no-code experiences. Prior to QuickSight he was the lead product manager for Inforiver, responsible for building a enterprise BI product from ground up. Bhupinder started his career in presales, followed by a small gig in consulting and then PM for xViz, an add on visualization product.