Model Zuora Data Using Azure Analysis Services

Microsoft Azure Analysis Services (AAS) is a fully-managed platform-as-a-service (PaaS) offering that delivers enterprise-grade data models in the cloud. When combined with CData Connect AI, AAS facilitates immediate cloud-to-cloud access to Zuora data for applications. This article outlines the process of connecting to Zuora via Connect AI and importing Zuora data into Visual Studio using an AAS extension.

CData Connect AI offers a seamless cloud-to-cloud interface tailored for Zuora, enabling you to create live models of Zuora data in Azure Analysis Services without the need to replicate data to a natively supported database. While constructing high-quality semantic data models for business reports and client applications, Azure Analysis Services formulates SQL queries to retrieve data. CData Connect AI is equipped with optimized data processing capabilities right from the start, directing all supported SQL operations, including filters and JOINs, directly to Zuora. This leverages server-side processing for swift retrieval of the requested Zuora data.

Prerequisites

Before you connect, you must first do the following:

• Connect a data source to your CData Connect AI account. Detailed steps are provided in the next section.
• Generate a Personal Access Token (PAT). Copy this down, as it acts as your password during authentication.
• Create a server in Azure Analysis Services to which you will deploy your data from CData Connect AI.
• Install and configure an On-Premise Gateway in your system. This will pull data from the source via CData Connect AI into the Azure Analysis Services project and deploy models to the server. Refer to the given link to find the detailed process.

Configure Zuora Connectivity for AAS

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

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "Zuora" from the Add Connection panel
👁 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 Visual Studio using Azure Analysis Services.

Connect to Zuora in Visual Studio Using AAS

The steps below outline connecting to CData Connect AI from Azure Analysis Services to create a new Zuora data source. You will need the Microsoft Analysis Services Project extension installed in Microsoft Visual Studio to continue.

1. In Visual Studio, create a new project. Select Analysis Services Tabular Project. Click on Next.
👁 Selecting Analysis Services Tabular Project

2. In the Configure your new project dialog box, enter a name for your project in the Project name field. Fill in the rest of the fields.
👁 Configure new project

3. Click on Create. The Tabular model designer dialog box opens. Select Workspace server and enter the address of your Azure Analysis Services server (for example, asazure://eastus.azure.windows.net/myAzureServer). Also, make sure to select the option SQL Server 2022 / Azure Analysis Services (1600) from the Compatibility level dropdown. Click on Test Connection to check if the connection details are correct. Click OK and sign in to your server.
👁 Adding AAS server

4. Now, click on OK to create the project. Your Visual Studio window should resemble the following screenshot:
👁 Visual Studio interface for creating the project

5. In the Tabular Model Explorer window of Visual Studio, right-click Data Sources and select Import From Data Source.
👁 Importing from the data source

6. In the Get Data window, select SQL Server database and click Connect. In the Server field, enter the Virtual SQL Server endpoint and the port separated by a comma: e.g., “tds.cdata.com, 14333”, and click on OK.
👁 Selecting SQL Server database
👁 Entering the virtual SQL server endpoint and port number

7. Click on Database and enter the following information:
   • 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: Enter the PAT you generated on the Settings page.

   Click on Connect. If successful, the Navigator window will pop up.

   👁 Entering the Username and Password (PAT)
   
8. In the Navigator window, search and select the tables of your choice 👁 Searching and selectisng the data source tables
   
9. You should now see the Salesforce table populated with data in the preview section on the right panel.
10. Click on Load to import the data. 👁 Select and load tables from the data source
    

Now that you have imported the Zuora data into your data model, you are ready to deploy the project to Azure Analysis Services for use in business reports, client applications, and more.

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