AWS sagemaker documentation change
Summary
Updated all references from 'Quick Suite' to 'Quick' throughout the documentation, including the title, steps, prerequisites, and links. This appears to be a branding change for the product name.
Security assessment
The changes are purely cosmetic/terminology updates without any security-related content modifications. No security vulnerabilities, configurations, or features were mentioned or altered. The updates focus solely on product naming consistency.
Diff
diff --git a/sagemaker/latest/dg/canvas-send-model-to-quicksight.md b/sagemaker/latest/dg/canvas-send-model-to-quicksight.md index 5f84753be..d64b2a5dd 100644 --- a//sagemaker/latest/dg/canvas-send-model-to-quicksight.md +++ b//sagemaker/latest/dg/canvas-send-model-to-quicksight.md @@ -5 +5 @@ -# Send your model to Quick Suite +# Send your model to Quick @@ -7 +7 @@ -If you use Quick Suite and want to leverage SageMaker Canvas in your Quick Suite visualizations, you can build an Amazon SageMaker Canvas model and use it as a _predictive field_ in your Quick Suite dataset. A _predictive field_ is a field in your Quick Suite dataset that can make predictions for a given column in your dataset, similar to how Canvas users make single or batch predictions with a model. To learn more about how to integrate Canvas predictive abilities into your Quick Suite datasets, see [SageMaker Canvas integration](https://docs.aws.amazon.com/quicksight/latest/user/sagemaker-canvas-integration.html) in the [Quick Suite User Guide](https://docs.aws.amazon.com/quicksight/latest/user/welcome.html). +If you use Quick and want to leverage SageMaker Canvas in your Quick visualizations, you can build an Amazon SageMaker Canvas model and use it as a _predictive field_ in your Quick dataset. A _predictive field_ is a field in your Quick dataset that can make predictions for a given column in your dataset, similar to how Canvas users make single or batch predictions with a model. To learn more about how to integrate Canvas predictive abilities into your Quick datasets, see [SageMaker Canvas integration](https://docs.aws.amazon.com/quicksight/latest/user/sagemaker-canvas-integration.html) in the [Quick User Guide](https://docs.aws.amazon.com/quicksight/latest/user/welcome.html). @@ -9 +9 @@ If you use Quick Suite and want to leverage SageMaker Canvas in your Quick Suite -The following steps explain how you can add a predictive field to your Quick Suite dataset using a Canvas model: +The following steps explain how you can add a predictive field to your Quick dataset using a Canvas model: @@ -13 +13 @@ The following steps explain how you can add a predictive field to your Quick Sui - 2. After building the model in Canvas, send the model to Quick Suite. A schema file automatically downloads to your local machine when you send the model to Quick Suite. You upload this schema file to Quick Suite in the next step. + 2. After building the model in Canvas, send the model to Quick. A schema file automatically downloads to your local machine when you send the model to Quick. You upload this schema file to Quick in the next step. @@ -15 +15 @@ The following steps explain how you can add a predictive field to your Quick Sui - 3. Open Quick Suite and choose a dataset with the same schema as the dataset you used to build your model. Add a predictive field to the dataset and do the following: + 3. Open Quick and choose a dataset with the same schema as the dataset you used to build your model. Add a predictive field to the dataset and do the following: @@ -21 +21 @@ The following steps explain how you can add a predictive field to your Quick Sui - 4. Save and publish your changes, and then generate predictions for the new dataset. Quick Suite uses the model to fill in the target column with predictions. + 4. Save and publish your changes, and then generate predictions for the new dataset. Quick uses the model to fill in the target column with predictions. @@ -26 +26 @@ The following steps explain how you can add a predictive field to your Quick Sui -In order to send a model from Canvas to Quick Suite, you must meet the following prerequisites: +In order to send a model from Canvas to Quick, you must meet the following prerequisites: @@ -28 +28 @@ In order to send a model from Canvas to Quick Suite, you must meet the following - * You must have both Canvas and Quick Suite set up. Your Quick Suite account must be created in the same AWS Region as your Canvas application. If your Quick Suite account’s home Region differs from your Canvas application’s Region, you must either [close](https://docs.aws.amazon.com/quicksight/latest/user/closing-account.html) and recreate your Quick Suite account, or [set up a Canvas application](https://docs.aws.amazon.com/sagemaker/latest/dg/canvas-getting-started.html#canvas-prerequisites) in the same Region as your Quick Suite account. Your Quick Suite account must also contain the default namespace, which you set up when you first create your Quick Suite account. Contact your administrator to help you get access to Quick Suite. For more information, see [Setting up for Quick Suite](https://docs.aws.amazon.com/quicksight/latest/user/setting-up.html) in the _Quick Suite User Guide_. + * You must have both Canvas and Quick set up. Your Quick account must be created in the same AWS Region as your Canvas application. If your Quick account’s home Region differs from your Canvas application’s Region, you must either [close](https://docs.aws.amazon.com/quicksight/latest/user/closing-account.html) and recreate your Quick account, or [set up a Canvas application](https://docs.aws.amazon.com/sagemaker/latest/dg/canvas-getting-started.html#canvas-prerequisites) in the same Region as your Quick account. Your Quick account must also contain the default namespace, which you set up when you first create your Quick account. Contact your administrator to help you get access to Quick. For more information, see [Setting up for Quick](https://docs.aws.amazon.com/quicksight/latest/user/setting-up.html) in the _Quick User Guide_. @@ -30 +30 @@ In order to send a model from Canvas to Quick Suite, you must meet the following - * Your user must have the necessary AWS Identity and Access Management (IAM) permissions to send your predictions to Quick Suite. Your administrator can set up the IAM permissions for your user. For more information, see [Grant Your Users Permissions to Send Predictions to Quick Suite](https://docs.aws.amazon.com/sagemaker/latest/dg/canvas-quicksight-permissions.html). + * Your user must have the necessary AWS Identity and Access Management (IAM) permissions to send your predictions to Quick. Your administrator can set up the IAM permissions for your user. For more information, see [Grant Your Users Permissions to Send Predictions to Quick](https://docs.aws.amazon.com/sagemaker/latest/dg/canvas-quicksight-permissions.html). @@ -32 +32 @@ In order to send a model from Canvas to Quick Suite, you must meet the following - * Quick Suite must have access to the Amazon S3 bucket that you’ve specified for Canvas application storage. For more information, see [Configure your Amazon S3 storage](./canvas-storage-configuration.html). + * Quick must have access to the Amazon S3 bucket that you’ve specified for Canvas application storage. For more information, see [Configure your Amazon S3 storage](./canvas-storage-configuration.html).