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URL: https://www.cdata.com/kb/tech/azuredatalake-spreadsheets-google-sheets.rst

⇱ Access Live Azure Data Lake Storage Data in Google Sheets through Connect Spreadsheets


Access Live Azure Data Lake Storage Data in Google Sheets through Connect Spreadsheets

πŸ‘ Cameron Leblanc
Cameron Leblanc
Senior Technology Evangelist
Use Connect Spreadsheets by CData to gain access to live Azure Data Lake Storage data from your Google Sheets.

Looking for Connect AI instructions?

Your Connect AI account includes Connect Spreadsheets, so you can use the instructions below. You can expect minor differences when referencing the Connect Spreadsheet platform, but the principles still apply!


Google Sheets is a web-based spreadsheet program provided by Google. When integrated with Connect Spreadsheets by CData, you can effortlessly gain access to Azure Data Lake Storage data directly within Google Sheets for tasks such as data analysis, collaboration, calculations, and more. This article offers a comprehensive guide on connecting to Azure Data Lake Storage within Connect Spreadsheets and accessing live Azure Data Lake Storage data seamlessly within Google Sheets.

Connect Spreadsheets is the easiest way to get all your live data into Microsoft Excel and Google Sheets - no more downloading, wrangling, and uploading files again. Just connect to your data, select the dataset you'd like to see, and import it into your spreadsheet.

This setup requires a Connect Spreadsheets account and the Connect Spreadsheets Add-On for Google Sheets. To get started, sign up a free Connect Spreadsheets account and install the free Connect Spreadsheets Google Sheets Add-On.


Configure Azure Data Lake Storage Connectivity for Google Sheets

Connectivity to Azure Data Lake Storage from Google Sheets is made possible through Connect Spreadsheets. To work with Azure Data Lake Storage data from Google Sheets, we start by creating and configuring a Azure Data Lake Storage connection.

  1. Log into Connect Spreadsheets, click Sources and click Add Connection πŸ‘ Adding a Connection
  2. Select "Azure Data Lake Storage" from the Add Connection panel πŸ‘ Selecting a data source
  3. Enter the necessary authentication properties to connect to Azure Data Lake Storage.

    Authenticating to a Gen 1 DataLakeStore Account

    Gen 1 uses OAuth 2.0 in Entra ID (formerly Azure AD) for authentication.

    For this, an Active Directory web application is required. You can create one as follows:

    1. Sign in to your Azure Account through the
    2. Select "Entra ID" (formerly Azure AD).
    3. Select "App registrations".
    4. Select "New application registration".
    5. Provide a name and URL for the application. Select Web app for the type of application you want to create.
    6. Select "Required permissions" and change the required permissions for this app. At a minimum, "Azure Data Lake" and "Windows Azure Service Management API" are required.
    7. Select "Key" and generate a new key. Add a description, a duration, and take note of the generated key. You won't be able to see it again.

    To authenticate against a Gen 1 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen1.
    • Account: Set this to the name of the account.
    • OAuthClientId: Set this to the application Id of the app you created.
    • OAuthClientSecret: Set this to the key generated for the app you created.
    • TenantId: Set this to the tenant Id. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.

    Authenticating to a Gen 2 DataLakeStore Account

    To authenticate against a Gen 2 DataLakeStore account, the following properties are required:

    • Schema: Set this to ADLSGen2.
    • Account: Set this to the name of the account.
    • FileSystem: Set this to the file system which will be used for this account.
    • AccessKey: Set this to the access key which will be used to authenticate the calls to the API. See the property for more information on how to acquire this.
    • Directory: Set this to the path which will be used to store the replicated file. If not specified, the root directory will be used.
    πŸ‘ Configuring a connection (OData is shown)
  4. Click Create & Test

With the connection configured, you are ready to connect to Azure Data Lake Storage data from Google Sheets.

Access Live Azure Data Lake Storage Data from Google Sheets

The steps below outline connecting to Connect Spreadsheets from Google Sheets to access live Azure Data Lake Storage data.

  1. Log into Google Sheets, create a new sheet (or open an existing one).
  2. Click Add-ons and click Get Add-ons (if you have already installed the Add-on, jump to step 5).
  3. Search for Connect Spreadsheets Add-On and install the Add-on. πŸ‘ Install the Add-On
  4. Authorize the Add-On. πŸ‘ Authorize the Add-On
  5. Back in Google Sheets, click Add-ons and open the Connect Spreadsheets Add-On. πŸ‘ Opening the Add-On
  6. In the Add-On panel, click "Log in" to sign into and authenticate with your Connect Spreadsheets account πŸ‘ Authenticating with Connect Spreadsheets
  7. In the Connect Spreadsheets panel in Google Sheets, click Import πŸ‘ Connect Spreadsheets panel in Google Sheets
  8. Choose a Connection (e.g. ADLS1), Table (e.g. Resources, and Columns to import πŸ‘ Choosing a Connection, Table, and Columns
  9. Optionally add Filters, Sorting, and a Limit πŸ‘ Filters, Sorting, Limits
  10. Click Execute to import the data and opt to overwrite the existing sheet or create a new one. πŸ‘ Opting where to import the data

Live Access to Azure Data Lake Storage Data from Cloud Applications

New, you have a direct, cloud-to-cloud connection to live Azure Data Lake Storage data from your Google Sheets workbook. You can add more data to your workbook for calculations, aggregations, collaboration, and more.

πŸ‘ Imported data (Salesforce is shown)

Try Connect Spreadsheets and get real-time data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications.