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Configuration overview

  • Статья

This article helps you configure Intelligent Recommendations.

Overview

Intelligent Recommendations has two integration points: the back-end integration the data service consumes and the front-end client integration via REST API.

The following diagram illustrates these integration points:

Example of Intelligent Recommendations flow from backend to frontend integration.

Prerequisites

Intelligent Recommendations uses Azure Data Lake Storage to read the incoming data and Microsoft Entra ID authentication for the API calls.

Before setting up Intelligent Recommendations, you must have access to your organization's Azure portal and access for elevated permissions. Make sure you have the following requirements:

  • Azure subscription. If you're new to Azure, go to Create your Azure free account today.

  • Microsoft Entra ID Tenant ID. For instructions, go to How to find your Microsoft Entra ID tenant ID.

  • Data Lake Storage account. For more information, go to Azure Data Lake Storage.

  • (Optional) Download the latest model.json file for Intelligent Recommendations data contracts: model.json.

    Note

    We strongly recommend doing the following:
    - Turn on diagnostics in Data Lake Storage
    - Create a separate Data Lake Storage for each environment.

    Important

    When onboarding to Intelligent Recommendations, data will be copied from your Data Lake Storage to the regions of the selected modeling resource. We advise you to set up the modeling resource in the same region as your Data Lake Storage account. If the Data Lake Storage account and modeling resources are in different regions, data will be copied from the Data Lake Storage region to the modeling resource region that you selected. Intelligent Recommendations currently resides in the following data centers: West US, West Europe (WEU), and SouthEast Asia (SEA).

Steps for onboarding Intelligent Recommendations

The onboarding process includes the following steps:

  1. Create a new Intelligent Recommendations account.

  2. Create a root directory for Intelligent Recommendations and share it with Intelligent Recommendations.

  3. Prepare the data for onboarding. For a full guide on how to prepare your data, go to Data contract overview.

  4. Add serving endpoint and modeling resources to the Intelligent Recommendations account.

See also

Use data contracts to share data
Configure Azure Data Lake Storage reports
Intelligent Recommendations REST API reference v1.0