Learn more about Azure Data Factory integration with the Intune Export API.
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By: Tanvi Bansal - Sr. Software Engineer
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Microsoft Intune is a cloud-based service that helps organizations manage and secure their mobile devices, apps, and data. Intune provides a variety of reports that help administrators monitor and troubleshoot the health and compliance of their devices and apps. These reports include device inventory, app inventory, device compliance, app protection, app configuration, and device configuration reports. Intune also offers a dashboard that shows the overall status and trends of the Intune service.
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In addition to the built-in reports, Intune also provides an export API that allows administrators to export Intune data to external systems for further analysis and reporting. The export API is a RESTful web service that supports the OData query syntax and returns data in JSON or .csv formats. The export API can be used to retrieve data on devices, apps, policies, assignments, and events. The export API can also be used to create custom reports that meet specific business needs or integrate with other reporting tools.
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For example, customers have used the export API to build custom reports for the following scenarios:
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You can read more about the Intune Export API and watch some great overview videos here:
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The export API is great for getting started on custom reporting, however enterprise customers frequently have centralized custom reporting solutions. In many cases they have existing data stores that they’d like to use and want to import Intune data exports into these solutions. They also don’t want to manually export and import data files.
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One possible solution for importing Intune data into existing data stores is to use Azure Data Factory, a cloud-based data integration service that orchestrates and automates the movement and transformation of data. Azure Data Factory can connect to various sources and destinations, including Intune export API, and create data pipelines that run on a specified schedule or trigger. Azure Data Factory also supports data transformation activities, such as mapping data columns, filtering data rows, or joining data sets. Azure Data Factory can enable administrators to create custom reports on Intune data by using their preferred data store and reporting tool.
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You can read more about Azure Data Factory here:
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This blog will show you how to combine Azure Data Factory and the Intune Export API to automate exporting reports and store them in Azure. You could then import this data into your data lakes or consume it directly via tools like Power BI.
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You’ll need a few prerequisites to follow this guide and complete configuration:
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Microsoft Entra tenant ID
The Entra tenant ID is needed to send requests to your tenant.
To find your Entra tenant ID, you can use one of the following methods:
An Enterprise app registration in Entra with Read permissions to relevant Intune data
The Entra app registration creates an application that allows Azure Data Factory activities to access your Intune data. To create an enterprise app registration in Entra with read permissions to Intune, follow these steps:
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Create a secret for your Entra app
A secret is a string that the app uses to prove its identity when requesting a token. To create a secret, follow these steps:
Azure Blob Storage and a container
Azure Blob Storage will be used to store the exported data, the container provides a location within the storage location to hold the files. You can use an existing storage account or create a new account by following the steps in Create a storage account – Azure Storage.
Note: For the purpose of this tutorial, you can use the default settings when configuring the account.
After your storage account is created, create a container by navigating to the Resource groups page and select the resource group that contains your storage account.
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Once an Azure blob storage and a container have been created, you can upload, download, and manage your blobs in the container using the Azure portal or other tools.
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Now that you’ve completed all the prerequisites you should have the following documented:
\nWith these completed we can now start working within the Azure Data Factory!
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Using the steps below we’ll create an Azure Pipeline that will perform the following activities:
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Follow each of the steps below. Note that most configuration issues are a result of typos or changes to object names. Throughout the tutorial we’ll use the “Debug” capability to test our pipeline end to end.
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\nThen drag connect the GetToken web activity to the new Set Variable activity by clicking on the “on success” green check mark and dragging the line to the Set Variable activity.
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{\n \"reportName\": \"DevicesWithInventory\",\n\n \"filter\": \"\",\n\n \"select\": [],\n\n \"format\": \"json\"\n\n}
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\nIn the expression builder enter “@concat('Bearer ',variables('Token'))”. Note there is a space after Bearer before the single quote. Ensure it passes validation and click OK.
\nCompleted configuration should look like this:
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If you have validation errors check naming for GetToken activity.
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\nEnter an export file name like “Export.json” and confirm the Import Schema setting is “None”.
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Now that the extracted JSON is in Azure Blob Storage, we can use another Copy to Activity to import the data to an Azure SQL server. Note that this step could vary based on your environment. Your team may already have SQL servers or another solution that they’d like to utilize. Check with your reporting teams to confirm the solution(s) for your environment and if Azure Data Factory supports it via the Copy activity. This article has a full table of supported configurations: Copy activity - Azure Data Factory & Azure Synapse.
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To complete the following steps you will need:
\nIt’s recommended that you provide your database team with a sample of the JSON export so they can design a table that matches the expected fields and data types that are in your report(s). This conversation should include how you plan on using the data and if you need historical trending, or just snapshot reporting.
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For this example (DevicesWithInventory) we’ve used this sample query to build the table, set data types/lengths, and add a column that shows the date/time that the records were inserted to assist with historic reporting. You will need to create different tables with unique columns/data types if you choose a different report:
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CREATE TABLE [DevicesWithInventory](\n\t[TimeStamp] [datetime2] NOT NULL DEFAULT (GetDate()),\n\t[DeviceId] [nvarchar](100) NOT NULL,\n\t[DeviceName] [nvarchar](100) NULL,\n\t[CreatedDate] [datetime2](7) NULL,\n\t[LastContact] [datetime2](7) NULL,\n\t[ReferenceId] [nvarchar](100) NULL,\n\t[OSVersion] [nvarchar](100) NULL,\n\t[GraphDeviceIsManaged] [bit] NULL,\n\t[EasID] [nvarchar](100) NULL,\n\t[SerialNumber] [nvarchar](100) NULL,\n\t[Manufacturer] [nvarchar](100) NULL,\n\t[Model] [nvarchar](100) NULL,\n\t[EasActivationStatus] [bit] NULL,\n\t[IMEI] [nvarchar](100) NULL,\n\t[EasLastSyncSuccessUtc] [datetime2](7) NULL,\n\t[EasStateReason] [nvarchar](100) NULL,\n\t[EasAccessState] [nvarchar](100) NULL,\n\t[InGracePeriodUntil] [datetime2](7) NULL,\n\t[AndroidPatchLevel] [nvarchar](100) NULL,\n\t[WifiMacAddress] [nvarchar](100) NULL,\n\t[MEID] [nvarchar](100) NULL,\n\t[SubscriberCarrierNetwork] [nvarchar](100) NULL,\n\t[StorageTotal] [int] NULL,\n\t[StorageFree] [int] NULL,\n\t[ManagedDeviceName] [nvarchar](100) NULL,\n\t[CategoryName] [nvarchar](100) NULL,\n\t[UserId] [nvarchar](100) NULL,\n\t[UPN] [nvarchar](100) NULL,\n\t[UserEmail] [nvarchar](100) NULL,\n\t[UserName] [nvarchar](100) NULL,\n\t[WiFiIPv4Address] [nvarchar](100) NULL,\n\t[WiFiSubnetID] [nvarchar](100) NULL,\n\t[CompliantState] [nvarchar](100) NULL,\n\t[ManagedBy] [nvarchar](100) NULL,\n\t[Ownership] [nvarchar](100) NULL,\n\t[DeviceState] [nvarchar](100) NULL,\n\t[DeviceRegistrationState] [nvarchar](100) NULL,\n\t[SupervisedStatusString] [nvarchar](100) NULL,\n\t[EncryptionStatusString] [nvarchar](100) NULL,\n\t[OS] [nvarchar](100) NULL,\n\t[SkuFamily] [nvarchar](100) NULL,\n\t[JoinType] [nvarchar](100) NULL,\n\t[PhoneNumber] [nvarchar](100) NULL,\n\t[JailBroken] [nvarchar](100) NULL,\n\t[ICCID] [nvarchar](100) NULL,\n\t[EthernetMAC] [nvarchar](100) NULL,\n\t[CellularTechnology] [nvarchar](100) NULL,\n\t[ProcessorArchitecture] [nvarchar](100) NULL,\n\t[EID] [nvarchar](100) NULL,\n\t[SystemManagementBIOSVersion] [nvarchar](100) NULL,\n\t[TPMManufacturerId] [nvarchar](100) NULL,\n\t[TPMManufacturerVersion] [nvarchar](100) NULL,\n\t[ProductName] [nvarchar](100) NULL,\n\t[CertExpirationDate] [nvarchar](100) NULL,\n)
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Open your existing pipeline and follow the steps below:
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\nThe names should resolve and now match the column names:
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\nAnd the data from the SQL table using SQL management studio.
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Now that you have the full pipeline running you can add a trigger to the pipeline that will cause the pipeline to run on a schedule. For example, if you want to run a device inventory export automatically at 8 AM each day.
\n\nClick on “+New”.
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Intune Export API is the recommended solution for easy bulk exports of data from your Intune tenant. It provides a quick method to extract a series of reports and is generally easier and more reliable than attempting to scrape the data via repeated direct Graph calls to the same endpoint.
\n
Azure Data Factory provides a solution that allows you to automate calls to the Export API and extract, store, and import that data into other locations including Azure Blob Storage, SQL Servers, and other locations.
Once the data is in SQL or other backend systems you could join it with other data sources and also consume it via analytics tools like PowerBI.
Share this tutorial with your teams to drive a discussion around the data that you need, how you’d like to structure it, where you’d like to store it, and then how you might consume the data.
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If you have any questions leave a comment below or reach out to us on X @IntuneSuppTeam!
","body@stringLength":"76884","rawBody":"By: Tanvi Bansal - Sr. Software Engineer
\n\n
Microsoft Intune is a cloud-based service that helps organizations manage and secure their mobile devices, apps, and data. Intune provides a variety of reports that help administrators monitor and troubleshoot the health and compliance of their devices and apps. These reports include device inventory, app inventory, device compliance, app protection, app configuration, and device configuration reports. Intune also offers a dashboard that shows the overall status and trends of the Intune service.
\n\n
In addition to the built-in reports, Intune also provides an export API that allows administrators to export Intune data to external systems for further analysis and reporting. The export API is a RESTful web service that supports the OData query syntax and returns data in JSON or .csv formats. The export API can be used to retrieve data on devices, apps, policies, assignments, and events. The export API can also be used to create custom reports that meet specific business needs or integrate with other reporting tools.
\n\n
For example, customers have used the export API to build custom reports for the following scenarios:
\n\n
You can read more about the Intune Export API and watch some great overview videos here:
\n\n
The export API is great for getting started on custom reporting, however enterprise customers frequently have centralized custom reporting solutions. In many cases they have existing data stores that they’d like to use and want to import Intune data exports into these solutions. They also don’t want to manually export and import data files.
\n\n
One possible solution for importing Intune data into existing data stores is to use Azure Data Factory, a cloud-based data integration service that orchestrates and automates the movement and transformation of data. Azure Data Factory can connect to various sources and destinations, including Intune export API, and create data pipelines that run on a specified schedule or trigger. Azure Data Factory also supports data transformation activities, such as mapping data columns, filtering data rows, or joining data sets. Azure Data Factory can enable administrators to create custom reports on Intune data by using their preferred data store and reporting tool.
\n\n
You can read more about Azure Data Factory here:
\n\n\n
This blog will show you how to combine Azure Data Factory and the Intune Export API to automate exporting reports and store them in Azure. You could then import this data into your data lakes or consume it directly via tools like Power BI.
\n\n
You’ll need a few prerequisites to follow this guide and complete configuration:
\n\n
Microsoft Entra tenant ID
The Entra tenant ID is needed to send requests to your tenant.
To find your Entra tenant ID, you can use one of the following methods:
An Enterprise app registration in Entra with Read permissions to relevant Intune data
The Entra app registration creates an application that allows Azure Data Factory activities to access your Intune data. To create an enterprise app registration in Entra with read permissions to Intune, follow these steps:
\n
\n
Create a secret for your Entra app
A secret is a string that the app uses to prove its identity when requesting a token. To create a secret, follow these steps:
Azure Blob Storage and a container
Azure Blob Storage will be used to store the exported data, the container provides a location within the storage location to hold the files. You can use an existing storage account or create a new account by following the steps in Create a storage account – Azure Storage.
Note: For the purpose of this tutorial, you can use the default settings when configuring the account.
After your storage account is created, create a container by navigating to the Resource groups page and select the resource group that contains your storage account.
\n
Once an Azure blob storage and a container have been created, you can upload, download, and manage your blobs in the container using the Azure portal or other tools.
\n
Now that you’ve completed all the prerequisites you should have the following documented:
\nWith these completed we can now start working within the Azure Data Factory!
\n\n
Using the steps below we’ll create an Azure Pipeline that will perform the following activities:
\n\n
Follow each of the steps below. Note that most configuration issues are a result of typos or changes to object names. Throughout the tutorial we’ll use the “Debug” capability to test our pipeline end to end.
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\n
\n
\n
\n
\n
\n
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\nThen drag connect the GetToken web activity to the new Set Variable activity by clicking on the “on success” green check mark and dragging the line to the Set Variable activity.
\n
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\n
\n
\n
\n
\n
\n
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\nIn the expression builder enter “@concat('Bearer ',variables('Token'))”. Note there is a space after Bearer before the single quote. Ensure it passes validation and click OK.
\nCompleted configuration should look like this:
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If you have validation errors check naming for GetToken activity.
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\nEnter an export file name like “Export.json” and confirm the Import Schema setting is “None”.
\n
\n
\n
\n
Now that the extracted JSON is in Azure Blob Storage, we can use another Copy to Activity to import the data to an Azure SQL server. Note that this step could vary based on your environment. Your team may already have SQL servers or another solution that they’d like to utilize. Check with your reporting teams to confirm the solution(s) for your environment and if Azure Data Factory supports it via the Copy activity. This article has a full table of supported configurations: Copy activity - Azure Data Factory & Azure Synapse.
\n\n
To complete the following steps you will need:
\nIt’s recommended that you provide your database team with a sample of the JSON export so they can design a table that matches the expected fields and data types that are in your report(s). This conversation should include how you plan on using the data and if you need historical trending, or just snapshot reporting.
\n
For this example (DevicesWithInventory) we’ve used this sample query to build the table, set data types/lengths, and add a column that shows the date/time that the records were inserted to assist with historic reporting. You will need to create different tables with unique columns/data types if you choose a different report:
\n
\n
\n
\n
\n
\n
\n
Open your existing pipeline and follow the steps below:
\n\n
\n
\n
\n
\n
\n
\n
\n
\nThe names should resolve and now match the column names:
\n
\nAnd the data from the SQL table using SQL management studio.
\n
Now that you have the full pipeline running you can add a trigger to the pipeline that will cause the pipeline to run on a schedule. For example, if you want to run a device inventory export automatically at 8 AM each day.
\n\nClick on “+New”.
\n
\n
Intune Export API is the recommended solution for easy bulk exports of data from your Intune tenant. It provides a quick method to extract a series of reports and is generally easier and more reliable than attempting to scrape the data via repeated direct Graph calls to the same endpoint.
\n
Azure Data Factory provides a solution that allows you to automate calls to the Export API and extract, store, and import that data into other locations including Azure Blob Storage, SQL Servers, and other locations.
Once the data is in SQL or other backend systems you could join it with other data sources and also consume it via analytics tools like PowerBI.
Share this tutorial with your teams to drive a discussion around the data that you need, how you’d like to structure it, where you’d like to store it, and then how you might consume the data.
\n
If you have any questions leave a comment below or reach out to us on X @IntuneSuppTeam!
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SvenV_ - Yes. Beat my old record or \"longest post ever\" by a few kilometers. Hard call on making it high level or providing a full walkthrough that anyone should be able to repeat. I will pass along the feedback to the reporting team on the Autopatch data.
Very interesting blogpost and might go for the longest blogpost so far? 😁
I believe using AutoPatch reporting data that is visible in the Intune portal is not possible/allowed to for exporting. As we are starting to use AutoPatch more with customers but would be nice to be able to export that data for external reporting so they don't need to access intune portal for the reporting part.
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