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Amazon QuickSight now makes it easier to connect with ML models from SageMaker and also introduces an enhanced SQL editor that simplifies building custom SQL-powered data sets.
You can integrate your Amazon SageMaker ML models with Amazon QuickSight to analyze augmented data and use it directly in your business intelligence dashboards. As a business analyst or data engineer you can leverage SageMaker and perform ML inference on your data and visualize on QuickSight with just a few click. QuickSight does the heavy lifting and removes the need to setup complex ETL to process data in and out of SageMaker and QuickSight. You can simply bring in your data sets into QuickSight and use Amazon SageMaker models within the QuickSight interface for different use cases, such as predicting the likelihood of customer churn, scoring leads to prioritize sales activity, and assessing credit risk for loan applications. See blog post here to learn more.
Amazon QuickSight also launched an enhanced SQL editor that simplifies creating data sets using custom SQL queries. The enhanced editor supports line numbers and color highlighting to call out syntax errors in the SQL statement. In addition to this, the editor provides a "Schema Explorer" which lets you explore schemas within your data source to find field names and types to reference when creating the custom SQL. See here to learn more.
Integration with SageMaker is available only on Enterprise Edition. Enhanced SQL editor is available in both Standard and Enterprise editions. Both these features are in all QuickSight regions - US East (N. Virginia and Ohio), US West (Oregon), EU (Frankfurt, Ireland and London), and Asia Pacific (Seoul, Singapore, Sydney and Tokyo).