Model Google Directory 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 Cloud, AAS facilitates immediate cloud-to-cloud access to Google Directory data for applications. This article outlines the process of connecting to Google Directory via Connect Cloud and importing Google Directory data into Visual Studio using an AAS extension.

CData Connect Cloud offers a seamless cloud-to-cloud interface tailored for Google Directory, enabling you to create live models of Google Directory 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 Cloud is equipped with optimized data processing capabilities right from the start, directing all supported SQL operations, including filters and JOINs, directly to Google Directory. This leverages server-side processing for swift retrieval of the requested Google Directory data.

Prerequisites

Before you connect, you must first do the following:

• Connect a data source to your CData Connect Cloud 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 Cloud.
• Install and configure an On-Premise Gateway in your system. This will pull data from the source via CData Connect Cloud into the Azure Analysis Services project and deploy models to the server. Refer to the given link to find the detailed process.

Configure Google Directory Connectivity for AAS

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

1. Log into Connect Cloud, click Connections and click Add Connection
2. Select "Google Directory" from the Add Connection panel
3. Enter the necessary authentication properties to connect to Google Directory.

   Google uses the OAuth authentication standard. You can authorize the data provider to access Google Spreadsheets as an individual user or with a Google Apps Domain service account. See the Getting Started section of the data provider help documentation for an authentication guide.

4. Click Create & Test
5. Navigate to the Permissions tab in the Add Google Directory Connection page and update the User-based permissions.

Add a Personal Access Token

If you are connecting from a service, application, platform, or framework that lacks support for OAuth authentication, you have the option to generate a Personal Access Token (PAT) for authentication purposes. It's advisable to follow best practices by creating a distinct PAT for each service to uphold access granularity.

1. Click on your username at the top right of the Connect Cloud app and click User Profile.
2. On the User Profile page, scroll down to the Personal Access Tokens section and click Create PAT.
3. Give your PAT a name and click Create.
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, you are ready to connect to Google Directory data from Visual Studio using Azure Analysis Services.

Connect to Google Directory in Visual Studio Using AAS

The steps below outline connecting to CData Connect Cloud from Azure Analysis Services to create a new Google Directory 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.
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.
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.
4. Now, click on OK to create the project. Your Visual Studio window should resemble the following screenshot:
5. In the Tabular Model Explorer window of Visual Studio, right-click Data Sources and select Import From 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.
7. Click on Database and enter the following information:
   • User name: Enter your CData Connect Cloud username. This is displayed in the top-right corner of the CData Connect Cloud 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.

8. In the Navigator window, search and select the tables of your choice
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.

Now that you have imported the Google Directory 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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