AWS sagemaker documentation change
Summary
Updated documentation to use 'QuickSight' instead of 'Amazon QuickSight' throughout the file for branding consistency
Security assessment
The changes are purely branding/naming convention updates (removing 'Amazon' prefix from QuickSight references). No security-related content was added, removed, or modified. Existing security requirements about IAM permissions and S3 bucket access remain unchanged.
Diff
diff --git a/sagemaker/latest/dg/canvas-send-model-to-quicksight.md b/sagemaker/latest/dg/canvas-send-model-to-quicksight.md index 1a4881fe7..725089156 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 Amazon QuickSight +# Send your model to QuickSight @@ -7 +7 @@ -If you use Amazon QuickSight and want to leverage SageMaker Canvas in your Amazon QuickSight visualizations, you can build an Amazon SageMaker Canvas model and use it as a _predictive field_ in your Amazon QuickSight dataset. A _predictive field_ is a field in your Amazon QuickSight 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 Amazon QuickSight datasets, see [SageMaker Canvas integration](https://docs.aws.amazon.com/quicksight/latest/user/sagemaker-canvas-integration.html) in the [Amazon QuickSight User Guide](https://docs.aws.amazon.com/quicksight/latest/user/welcome.html). +If you use QuickSight and want to leverage SageMaker Canvas in your QuickSight visualizations, you can build an Amazon SageMaker Canvas model and use it as a _predictive field_ in your QuickSight dataset. A _predictive field_ is a field in your QuickSight 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 QuickSight datasets, see [SageMaker Canvas integration](https://docs.aws.amazon.com/quicksight/latest/user/sagemaker-canvas-integration.html) in the [QuickSight User Guide](https://docs.aws.amazon.com/quicksight/latest/user/welcome.html). @@ -9 +9 @@ If you use Amazon QuickSight and want to leverage SageMaker Canvas in your Amazo -The following steps explain how you can add a predictive field to your Amazon QuickSight dataset using a Canvas model: +The following steps explain how you can add a predictive field to your QuickSight dataset using a Canvas model: @@ -13 +13 @@ The following steps explain how you can add a predictive field to your Amazon Qu - 2. After building the model in Canvas, send the model to Amazon QuickSight. A schema file automatically downloads to your local machine when you send the model to Amazon QuickSight. You upload this schema file to Amazon QuickSight in the next step. + 2. After building the model in Canvas, send the model to QuickSight. A schema file automatically downloads to your local machine when you send the model to QuickSight. You upload this schema file to QuickSight in the next step. @@ -15 +15 @@ The following steps explain how you can add a predictive field to your Amazon Qu - 3. Open Amazon QuickSight 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 QuickSight 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 Amazon Qu - 4. Save and publish your changes, and then generate predictions for the new dataset. Amazon QuickSight 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. QuickSight 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 Amazon Qu -In order to send a model from Canvas to Amazon QuickSight, you must meet the following prerequisites: +In order to send a model from Canvas to QuickSight, you must meet the following prerequisites: @@ -28 +28 @@ In order to send a model from Canvas to Amazon QuickSight, you must meet the fol - * You must have both Canvas and Amazon QuickSight set up. Your Amazon QuickSight account must be created in the same AWS Region as your Canvas application. If your Amazon QuickSight 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 Amazon QuickSight 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 Amazon QuickSight account. Your Amazon QuickSight account must also contain the default namespace, which you set up when you first create your Amazon QuickSight account. Contact your administrator to help you get access to Amazon QuickSight. For more information, see [Setting up for Amazon QuickSight](https://docs.aws.amazon.com/quicksight/latest/user/setting-up.html) in the _Amazon QuickSight User Guide_. + * You must have both Canvas and QuickSight set up. Your QuickSight account must be created in the same AWS Region as your Canvas application. If your QuickSight 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 QuickSight 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 QuickSight account. Your QuickSight account must also contain the default namespace, which you set up when you first create your QuickSight account. Contact your administrator to help you get access to QuickSight. For more information, see [Setting up for QuickSight](https://docs.aws.amazon.com/quicksight/latest/user/setting-up.html) in the _QuickSight User Guide_. @@ -30 +30 @@ In order to send a model from Canvas to Amazon QuickSight, you must meet the fol - * Your user must have the necessary AWS Identity and Access Management (IAM) permissions to send your predictions to Amazon QuickSight. Your administrator can set up the IAM permissions for your user. For more information, see [Grant Your Users Permissions to Send Predictions to Amazon QuickSight](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 QuickSight. Your administrator can set up the IAM permissions for your user. For more information, see [Grant Your Users Permissions to Send Predictions to QuickSight](https://docs.aws.amazon.com/sagemaker/latest/dg/canvas-quicksight-permissions.html). @@ -32 +32 @@ In order to send a model from Canvas to Amazon QuickSight, you must meet the fol - * Amazon QuickSight 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). + * QuickSight 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).