![]() Next to the workflow you'd like to delete, select the vertical ellipsis (⋮) and select Delete. If you don't have such a column in your data set, choose an attribute that uniquely identifies the row. Choose an attribute from the inference output with values similar to the Customer ID column of the Customer table. Then, select Next.įor Model Output Parameters, change any of the following:Ĭhange the matching attribute from Customer ID in results to identify customers. Next to the workflow you'd like to update, select the vertical ellipsis (⋮) and select Edit.Ĭhange Display name if needed, and select Next.įor each Web service input, update the matching Table from Customer Insights, if needed. Select a workflow to view available actions. Go to Insights > Custom models to view the workflows you created. Your workflow also runs automatically with every scheduled refresh. Select the vertical ellipsis (⋮) for the workflow and select Run. Customer Insights will get a Contributor role on the Azure workspace. If you configured a workflow for an Azure Machine Learning pipeline, Customer Insights attaches to the workspace that contains the pipeline. ![]() The Workflow Saved screen displays details about the workflow. Select the matching attribute from Customer ID in results that identifies customers and select Save. Output Path parameter name of your batch pipeline.Output data store parameter name of your batch pipeline.Table name for the pipeline output results.You'll see an error if a web service field can't be mapped to a table.įor Model Output Parameters, set the following properties: The custom model workflow will apply heuristics to map the web service input fields to the table attributes based on the name and data type of the field. Learn more about publishing a pipeline in Azure Machine Learning using the designer or SDK.įor each Web service input, select the matching Table from Customer Insights. Select the Workspaces associated with your web service.Ĭhoose the Azure Machine Learning pipeline in the Web service that contains your model dropdown. If your Azure Machine Learning subscription is in a different tenant than Customer Insights, select Sign in with your credentials for the selected organization. Select the organization that contains the web service in Tenant that contains your web service. ![]() Go to Insights > Custom models and select New workflow. When you transfer data to an Azure service, please ensure that service is configured to process data in the manner and location necessary to comply with any legal or regulatory requirements for that data for your organization. Pipeline must be published under a pipeline endpoint.Īn Azure Data Lake Gen2 storage account associated with your Azure Studio instance.įor Azure Machine Learning workspaces with pipelines, Owner or User Access Administrator permissions to the Azure Machine Learning Workspace.ĭata is transferred between your Customer Insights instances and the selected Azure web services or pipelines in the workflow. Web services published through Azure Machine Learning batch pipelines. For more information about building custom ML models, see Use Azure Machine Learning-based models. Workflows help you choose the data you want to generate insights from and map the results to your unified customer data. For more information, see Migrate to Azure Machine Learning.Ĭustom models lets you manage workflows based on Azure Machine Learning models. Through 31 August 2024, you can continue to use the existing Machine Learning Studio (classic) resources. ![]() We recommend you transition to Azure Machine Learning by that date.īeginning 1 December 2021, you will not be able to create new Machine Learning Studio (classic) resources. Support for Machine Learning Studio (classic) will end on 31 August 2024.
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