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Using the job ID and message ID returned by the previous request, the client connects to the WebSocket API and sends the job ID and message ID to the WebSocket connection. A Lambda function invokes the Amazon Textract API DetectDocument to parse tabular data from source documents and stores extracted data into DynamoDB.
Wipro has used the input filter and join functionality of SageMaker batch transformation API. The response is returned to Lambda and sent back to the application through API Gateway. Use QuickSight refresh dataset APIs to automate the spice data refresh. Implement group-based security for dashboard and analysis access control.
Such manual efforts are especially challenging for large-scale, multinational business organizations that require revenue forecasts across a wide range of product groups and geographical areas at multiple levels of granularity. Any automated forecasting solution needs to provide forecasts at any arbitrary level of business-line aggregation.
For instructions on assigning permissions to the role, refer to Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference. Run the following cells to create your feature group name. After running a few more cells in the code, the feature group is successfully created. event_time_feature_name = "EventTime".
References More information is available at the following resources: Automate Amazon SageMaker Studio setup using AWS CDK AWS SageMaker CDK API reference About the Authors Zdenko Estok works as a cloud architect and DevOps engineer at Accenture. Shikhar enjoys playing guitar, composing music, and practicing mindfulness in his spare time.
For instructions on assigning permissions to the role, refer to Amazon SageMaker API Permissions: Actions, Permissions, and Resources Reference. Model groups This tab lists groups of model versions that were created by pipeline runs in the project. You can choose the model group to access the latest version of the model.
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