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URL: https://www.cdata.com/kb/tech/zuora-cloud-adf.rst

⇱ Import Zuora Data Using Azure Data Factory

Import Zuora Data Using Azure Data Factory

👁 Dibyendu Datta
Dibyendu Datta
Lead Technology Evangelist
Use CData Connect AI to connect to Zuora Data from Azure Data Factory and import live Zuora data.

Microsoft Azure Data Factory (ADF) is a completely managed, serverless data integration service. When combined with CData Connect AI, ADF enables immediate cloud-to-cloud access to Zuora data within data flows. This article outlines the process of connecting to Zuora through Connect AI and accessing Zuora data within ADF.

CData Connect AI offers a cloud-to-cloud interface tailored for Zuora, granting you the ability to access live data from Zuora data within Azure Data Factory without the need for data replication to a natively supported database. Equipped with optimized data processing capabilities by default, CData Connect AI seamlessly channels all supported SQL operations, including filters and JOINs, directly to Zuora. This harnesses server-side processing to expedite the retrieval of the desired Zuora data.

Configure Zuora Connectivity for ADF

Connectivity to Zuora from Azure Data Factory is made possible through CData Connect AI. To work with Zuora data from Azure Data Factory, we start by creating and configuring a Zuora connection.

CData Connect AI uses a straightforward, point-and-click interface to connect to data sources.

  1. Log into Connect AI, click Sources, and then click Add Connection
    2. 👁 Adding a Connection
  2. Select "Zuora" from the Add Connection panel
    3. 👁 Selecting a data source
  3. Enter the necessary authentication properties to connect to Zuora.

    Zuora uses the OAuth standard to authenticate users. See the online Help documentation for a full OAuth authentication guide.

    Configuring Tenant property

    In order to create a valid connection with the provider you need to choose one of the Tenant values (USProduction by default) which matches your account configuration. The following is a list with the available options:

    • USProduction: Requests sent to https://rest.zuora.com.
    • USAPISandbox: Requests sent to https://rest.apisandbox.zuora.com"
    • USPerformanceTest: Requests sent to https://rest.pt1.zuora.com"
    • EUProduction: Requests sent to https://rest.eu.zuora.com"
    • EUSandbox: Requests sent to https://rest.sandbox.eu.zuora.com"

    Selecting a Zuora Service

    Two Zuora services are available: Data Query and AQuA API. By default ZuoraService is set to AQuADataExport.

    DataQuery

    The Data Query feature enables you to export data from your Zuora tenant by performing asynchronous, read-only SQL queries. We recommend to use this service for quick lightweight SQL queries.

    Limitations
    • The maximum number of input records per table after filters have been applied: 1,000,000
    • The maximum number of output records: 100,000
    • The maximum number of simultaneous queries submitted for execution per tenant: 5
    • The maximum number of queued queries submitted for execution after reaching the limitation of simultaneous queries per tenant: 10
    • The maximum processing time for each query in hours: 1
    • The maximum size of memory allocated to each query in GB: 2
    • The maximum number of indices when using Index Join, in other words, the maximum number of records being returned by the left table based on the unique value used in the WHERE clause when using Index Join: 20,000

    AQuADataExport

    AQuA API export is designed to export all the records for all the objects ( tables ). AQuA query jobs have the following limitations:

    Limitations
    • If a query in an AQuA job is executed longer than 8 hours, this job will be killed automatically.
    • The killed AQuA job can be retried three times before returned as failed.
    👁 Configuring a connection (Salesforce is shown)
  4. Click Save & Test
  5. Navigate to the Permissions tab in the Add Zuora Connection page and update the User-based permissions. 👁 Updating permissions

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

  1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
  2. On the Settings page, go to the Access Tokens section and click Create PAT.
  3. Give the PAT a name and click Create. 👁 Creating a new PAT
  4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Zuora data from Azure Data Factory.

Access Live Zuora Data in Azure Data Factory

To establish a connection from Azure Data Factory to the CData Connect AI Virtual SQL Server API, follow these steps.

  1. Login to Azure Data Factory.
    2. 👁 Logging in to ADF
  2. If you have not yet created a Data Factory, Click New -> Dataset.
    3. 👁 Creating new data factory
  3. In the search bar, enter SQL Server and select it when it appears. On the following screen, enter a name for the server. In the Linked service field, select New.
    4. 👁 Selecting SQL Server
  4. Enter the connection settings.
    • Name - enter a name of your choice.
    • Server name - enter the Virtual SQL Server endpoint and port separated by a comma: tds.cdata.com,14333
    • Database name - enter the Connection Name of the CData Connect AI data source you want to connect to (for example, Zuora1).
    • User Name - enter your CData Connect AI username. This is displayed in the top-right corner of the CData Connect AI interface. For example, [email protected].
    • Password - select Password (not Azure Key Vault) and enter the PAT you generated on the Settings page.
    • Click Create.
    5. 👁 Configuring new linked service
  5. In Set properties, set the Name, choose the Linked service we just created, select a Table name from those available, and Import schema from connection/store. Click OK.
    6. 👁 Setting the properties
  6. After creating the linked service, the following screen should appear:
    7. 👁 Displaying the new screen
  7. Click preview data to see the imported Zuora table.
    8. 👁 Previewing the imported table
    You can now use this dataset when creating data flows in Azure Data Factory.

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