Google Sheets Connector for Azure Data Factory (Pipeline) In this article you will learn how to integrate Google Sheets data in Azure Data Factory (Pipeline) without coding in just a few clicks (live / bi-directional connection to Google Sheets). Read / write Google Sheets data inside your app, perform many Google Sheets operations without coding using easy to use high performance API Connector for Google Sheets. Using Google Sheets Connector you will be able to connect, read, and write data from within Azure Data Factory (Pipeline). Follow the steps below to see how we would accomplish that. Download Documentation The driver mentioned above is part of ODBC PowerPack which is a collection of high-performance Drivers for various API data source (i.e. REST API, JSON, XML, CSV, Amazon S3 and many more). Using familiar SQL query language you can make live connections and read/write data from API sources or JSON / XML / CSV Files inside SQL Server (T-SQL) or your favorite Reporting (i.e. Power BI, Tableau, Qlik, SSRS, MicroStrategy, Excel, MS Access), ETL Tools (i.e. Informatica, Talend, Pentaho, SSIS). You can also call our drivers from programming languages such as JAVA, C#, Python, PowerShell etc. If you are new to ODBC and ZappySys ODBC PowerPack then check the following links to get started. ODBC PowerPack - System Requirements and Installation Getting Started - Using ODBC PowerPack ODBC API Driver Help File

Connect to Google Sheets in other apps Connect to Google Sheets in SSIS Connect to Google Sheets in SQL Server Connect to Google Sheets in Power BI Connect to Google Sheets in SSRS Connect to Google Sheets in Informatica Connect to Google Sheets in MS Access Connect to Google Sheets in MS Excel Connect to Google Sheets in SSAS Connect to Google Sheets in C# Connect to Google Sheets in Python Connect to Google Sheets in JAVA Connect to Google Sheets in Tableau Connect to Google Sheets in SAP Crystal Reports Connect to Google Sheets in Azure Data Factory (SSIS) Connect to Google Sheets in Talend Studio Connect to Google Sheets in UiPath Connect to Google Sheets in PowerShell Connect to Google Sheets in ODBC

Create ODBC Data Source (DSN) based on ZappySys API Driver

Step-by-step instructions

To get data from Google Sheets using Azure Data Factory (Pipeline) we first need to create a DSN (Data Source) which will access data from Google Sheets. We will later be able to read data using Azure Data Factory (Pipeline). Perform these steps:

1. Install ZappySys ODBC PowerPack.

2. Open ODBC Data Sources (x64):
   

3. Create a System Data Source (System DSN) based on ZappySys API Driver

   ZappySys API Driver

   
   You should create a System DSN (instead of a User DSN) if the client application is launched under a Windows System Account, e.g. as a Windows Service. If the client application is 32-bit (x86) running with a System DSN, use ODBC Data Sources (32-bit) instead of the 64-bit version. Furthermore, a User DSN may be created instead, but then you will not be able to use the connection from Windows Services(or any application running under a Windows System Account).

4. When the Configuration window appears give your data source a name if you haven't done that already, then select "Google Sheets" from the list of Popular Connectors. If "Google Sheets" is not present in the list, then click "Search Online" and download it. Then set the path to the location where you downloaded it. Finally, click Continue >> to proceed with configuring the DSN:

   GoogleSheetsDSN

   Google Sheets

   

5. Now it's time to configure the Connection Manager. Select Authentication Type, e.g. Token Authentication. Then select API Base URL (in most cases, the default one is the right one). More info is available in the Authentication section.

    User Account [OAuth]

   Steps to get Google Sheets Credentials
   This connection can be configured in two ways. Use Default App (Created by ZappySys) OR Use Custom App created by you.
   To use minimum settings you can start with the ZappySys created App. Just change UseCustomApp=false on the properties grid so you dont need ClientID / Secret. When you click Generate Token you might see a warning about App is not trusted (Simply Click Advanced Link to expand hidden section and then click Go to App link to Proceed).

   To register a custom app, perform the following steps (Detailed steps found in the help link at the end):

   1. Go to Google API Console.
   2. From the Project Dropdown (usually found at the top bar) click Select Project.
   3. On the Project Popup click CREATE PROJECT.
   4. Once the project is created you can click Select Project to switch the context (You can click on Notification link or Choose from Top Dropdown).
   5. Click ENABLE APIS AND SERVICES.
   6. Now we need to Enable two APIs one by one (Sheets API and Drive API).
   7. Search Sheets. Select and click ENABLE.
   8. Search Drive. Select and click ENABLE.
   9. Go back to the main screen of the Google API Console
   10. Click the OAuth Consent Screen tab. Enter necessary details and Save.
   11. Click the Credentials tab.
   12. Click CREATE CREDENTIALS (some where in topbar) and select OAuth Client ID option.
   13. When prompted Select Application Type as Desktop App and click Create to receive your ClientID and Secret. Later on you can use this information now to configure Connection with UseCustomApp=true.
       NOTE: If you are planning to use your current data connection/token for automated processes, we recommend that you use a generic account for token generation when the login box appears (e.g. sales_automation@mycompany.com instead of bob_smith@mycompany.com). When you use a personal account which is tied to a specific employee profile and that employee leaves the company, the token may become invalid and any automated processes using that token will fail. Another potentially unwanted effect of using a personal token is incorrect logging; the API calls (e.g. Read, Edit, Delete, Upload) made with that token will record the specific user as performing the calls instead of an automated process.
   14. Go to OAuth Consent Screen tab. Under Publishing Status click PUBLISH APP to ensure your refresh token doesnt expire often. If you planning to use App for Private use then do not have to worry about Verification Status after Publish.

   Fill in all required parameters and set optional parameters if needed:

   GoogleSheetsDSN

   Google Sheets

   User Account [OAuth]

   https://sheets.googleapis.com/v4/spreadsheets

   Required Parameters
   UseCustomApp	Fill in the parameter...
   Default SpreadSheetId	Fill in the parameter...
   Optional Parameters
   ClientId	Fill in the parameter...
   ClientSecret	Fill in the parameter...
   Scope	Fill in the parameter...
   Default Tab Name (i.e. Sheet1)	Fill in the parameter...
   RetryMode	Fill in the parameter...
   RetryStatusCodeList	Fill in the parameter...
   RetryCountMax	Fill in the parameter...
   Redirect URL (Only for Web App)	Fill in the parameter...

   

    Service Account (Using Private Key File) [OAuth]

   Steps to get Google Sheets Credentials
   Use these steps to authenticate as service account rather than Google / GSuite User. Learn more about service account here

   Basically to call Google API as Service account we need to perform following steps listed in 3 sections (Detailed steps found in the help link at the end)

   Create Project

   First thing is create a Project so we can call Google API. Skip this section if you already have Project (Go to next section)

   1. Go to Google API Console
   2. From the Project Dropdown (usually found at the top bar) click Select Project
   3. On Project Propup click CREATE PROJECT
   4. Once project is created you can click Select Project to switch the context (You can click on Notification link or Choose from Top Dropdown)
   5. Click ENABLE APIS AND SERVICES
   6. Now we need to Enable two APIs one by one (Sheets API and Drive API).
   7. Search Sheets. Select and click ENABLE
   8. Search Drive. Select and click ENABLE

   Create Service Account

   Once Project is created and APIs are enabled we can now create a service account under that project. Service account has its ID which looks like some email ID (not to confuse with Google /Gmail email ID)

   1. Go to Create Service Account
   2. From the Project Dropdown (usually found at the top bar) click Select Project
   3. Enter Service account name and Service account description
   4. For Role, do not select anything for now and Click Continue and then click Done. Next we will create Key.

   Create Key

   Once service account is created we need to create key file (i.e. credentials).

   1. In the Cloud Console, click the email address for the service account that you created.
   2. Click Keys.
   3. Click Add key, then click Create new key.
   4. Click Create and select P12 format. A P12 key file is downloaded to your computer. We will use this file in our API connection.
   5. Click Close.
   6. Now you may use downloaded *.p12 key file as secret file and Service Account Email as Client ID (e.g. some-service-account-name@your-project-id.iam.gserviceaccount.com ).

   Add Permission

   Now last thing is give read/write permission to Service Account. Basically you can create or open Google Sheet and add the Service Account as an editor to it as below.

   1. Copy the email address of your service account we created in previous step (its usually like this some-service-account-name@your-project-id.iam.gserviceaccount.com).
   2. Create or select an existing Google Sheet.
   3. Navigate to Sheet for which you like to give read/write access to Service Account.
   4. Click on the Share button in the top right, and add the email address of the service account as an editor. Here is how to share file(s) with specific people. Juse share with Service Account (use Service Account Email found on previous section)

   Fill in all required parameters and set optional parameters if needed:

   GoogleSheetsDSN

   Google Sheets

   Service Account (Using Private Key File) [OAuth]

   https://sheets.googleapis.com/v4/spreadsheets

   Required Parameters
   Service Account Email	Fill in the parameter...
   Service Account Private Key Path (i.e. *.p12)	Fill in the parameter...
   Default SpreadSheetId	Fill in the parameter...
   Optional Parameters
   Scope	Fill in the parameter...
   Default Tab Name (i.e. Sheet1)	Fill in the parameter...
   RetryMode	Fill in the parameter...
   RetryStatusCodeList	Fill in the parameter...
   RetryCountMax	Fill in the parameter...

   

6. Once the data source has been configured, you can preview data. Select the Preview tab and use settings similar to the following to preview data:
   

7. Click OK to finish creating the data source.

Video instructions

Read data in Azure Data Factory (ADF) from ODBC datasource (Google Sheets)

1. To start press New button:

   

2. Select "Azure, Self-Hosted" option:

   

3. Select "Self-Hosted" option:

   

4. Set a name, we will use "OnPremisesRuntime":

   

5. Download and install Microsoft Integration Runtime.

6. Launch Integration Runtime and copy/paste Authentication Key from Integration Runtime configuration in Azure Portal:

   

7. After finishing registering the Integration Runtime node, you should see a similar view:

   

8. Go back to Azure Portal and finish adding new Integration Runtime. You should see it was successfully added:

   

9. Go to Linked services section and create a new Linked service based on ODBC:

   

10. Select "ODBC" service:

    

11. Configure new ODBC service. Use the same DSN name we used in the previous step and copy it to Connection string box:

    GoogleSheetsDSN

    DSN=GoogleSheetsDSN

    

12. For created ODBC service create ODBC-based dataset:

    

13. Go to your pipeline and add Copy data connector into the flow. In Source section use OdbcDataset we created as a source dataset:

    

14. Then go to Sink section and select a destination/sink dataset. In this example we use precreated AzureBlobStorageDataset which saves data into an Azure Blob:

    

15. Finally, run the pipeline and see data being transferred from OdbcDataset to your destination dataset:

    

Advanced topics

Create Custom Stored Procedure in ZappySys Driver

You can create procedures to encapsulate custom logic and then only pass handful parameters rather than long SQL to execute your API call.

Steps to create Custom Stored Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here

1. Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
   

2. Enter the desired Procedure name and click on OK:
   

3. Select the created Stored Procedure and write the your desired stored procedure and Save it and it will create the custom stored procedure in the ZappySys Driver:
   Here is an example stored procedure for ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
   

   CREATE PROCEDURE [usp_get_orders]
       @fromdate = '<<yyyy-MM-dd,FUN_TODAY>>'
    AS
       SELECT * FROM Orders where OrderDate >= '<@fromdate>';
   

   
   

4. That's it now go to Preview Tab and Execute your Stored Procedure using Exec Command. In this example it will extract the orders from the date 1996-01-01:
   

   Exec usp_get_orders '1996-01-01';

   
   

5. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC usp_get_orders @fromdate=''1996-07-30''')

   
   

6. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Create Custom Virtual Table in ZappySys Driver

ZappySys API Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

If you're dealing with Microsoft Access and need to import data from an SQL query, it's important to note that Access doesn't allow direct import of SQL queries. Instead, you can create custom objects (Virtual Tables) to handle the import process.

Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 URLs with slight variations you can create virtual tables with just URL as Parameter setting.

1. Go to Custom Objects Tab and Click on Add button and Select Add Table:
   

2. Enter the desired Table name and click on OK:
   

3. And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.

4. Select the created table, Select Text Type AS SQL and write the your desired SQL Query and Save it and it will create the custom table in the ZappySys Driver:
   Here is an example SQL query for ZappySys Driver. You can insert Placeholders also. Read more about placeholders here
   

   SELECT
     "ShipCountry",
     "OrderID",
     "CustomerID",
     "EmployeeID",
     "OrderDate",
     "RequiredDate",
     "ShippedDate",
     "ShipVia",
     "Freight",
     "ShipName",
     "ShipAddress",
     "ShipCity",
     "ShipRegion",
     "ShipPostalCode"
   FROM "Orders"
   Where "ShipCountry"='USA'

   
   

5. That's it now go to Preview Tab and Execute your custom virtual table query. In this example it will extract the orders for the USA Shipping Country only:
   

   SELECT * FROM "vt__usa_orders_only"

   
   

6. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC [usp_get_orders] ''1996-01-01''')

   
   

7. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Actions supported by Google Sheets Connector

Google Sheets Connector Examples for Azure Data Factory (Pipeline) Connection

This page offers a collection of SQL examples designed for seamless integration with the ZappySys API ODBC Driver under ODBC Data Source (36/64) or ZappySys Data Gateway, enhancing your ability to connect and interact with Prebuilt Connectors effectively.

SELECT * FROM [Sheet1]

SELECT * FROM [Class Data] WITH(SpreadSheetId='1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms')

SELECT * FROM [Class Data]
WITH(
	  Range='A4:GR'  --cell range you like to query
	, ArrayTransEnableCustomColumns='False' --do not treat first row in range as Column Names
	, SpreadSheetId='1BxiMVs0XRA5nFMdKvBdBZjgmUUqptlbs74OgvE2upms'  --enter sheet id you like to query. Comment this if you like to use default ID defined in the connection
)

UPDATE [Sheet1]
SET Col1='data-1', Col2=100, Col3='2020-01-31' --column names are ignored. Values are sent in the same order you supply and writtern to start cell specified by WriteRange
WITH(
	, WriteRange='G9' --start writing from here
	, SpreadSheetId='1az2H8ZYk7BvjddVTqPR-LfDjX9IRpIpjCDpFPe9EzkU' --comment this to use default Sheet Id from connection setting
)

UPDATE [Sheet1]
SOURCE(
 'ODBC',  --driver type ODBC | MSSQL | OLEDB
 'Driver={ZappySys CSV Driver};', --connection string for driver
 'SELECT * FROM $ WITH (SRC=''c:\data.csv'') ' --sql query for source data
)
WITH(
  WriteRange='G9', SpreadSheetId='1az2H8ZYk7BvjddVTqPR-LfDjX9IRpIpjCDpFPe9EzkU' --comment this to use default Sheet Id from connection setting 
)

UPDATE [Sheet1]
SET Col1='Jan',Col2='Feb',Col3='Mar'
WITH(
  WriteRange='G9', 
  SpreadSheetId='1az2H8ZYk7BvjddVTqPR-LfDjX9IRpIpjCDpFPe9EzkU', --comment this to use default Sheet Id from connection setting
  MajorDimension='COLUMNS' --write values vertical rather horizontal
)

INSERT INTO "Sheet1"("MyStringCol", "MyIntegerCol", "MyDateCol", "MyDecimalCol") VALUES('AAA',100,'2020-01-01',150.33)

INSERT INTO [Sheet1]
SOURCE(
 'ODBC', --driver type ODBC | MSSQL | OLEDB
 'Driver={ZappySys CSV Driver};', --connection string for driver
 'SELECT * FROM $ WITH (SRC=''c:\temp\dump.txt'') ' --sql query for source data
)
WITH(
  Range='G9', SpreadSheetId='1az2H8ZYk7BvjddVTqPR-LfDjX9IRpIpjCDpFPe9EzkU' --comment this to use default Sheet Id from connection setting 
)

INSERT INTO [Sheet1](Col1,Col2,Col3) 
VALUES('Jan','Feb','Mar')
WITH(
  Range='G9', --starting cell to write data
  SpreadSheetId='1az2H8ZYk7BvjddVTqPR-LfDjX9IRpIpjCDpFPe9EzkU', --comment this to use default Sheet Id from connection setting
  MajorDimension='COLUMNS' --write values vertical rather horizontal
)

SELECT * FROM batch_update_request
WITH(
	  Body='{
  "requests": [
    {
      "deleteDimension": {
        "range": {
          "sheetId": 0,
          "dimension": "ROWS",
          "startIndex": 10,
          "endIndex": 20
        }
      }
    } ,
    
   {
      "deleteDimension": {
        "range": {
          "sheetId": 0,
          "dimension": "ROWS",
          "startIndex": 50,
          "endIndex": 60
        }
      }
    }
    
  ]
}'
	, TabId='0' -- tab internal id (use UI to get this). 0 means first tab. Or check URL in browser and see at the end of URL #gid=xxxxxxx where xxxxxx is your tab id
	, SpreadSheetId='1az2H8ZYk7BvjddVTqPR-LfDjX9IRpIpjCDpFPe9EzkU' --comment this to use default Sheet Id from connection setting
)

Conclusion

In this article we discussed how to connect to Google Sheets in Azure Data Factory (Pipeline) and integrate data without any coding. Click here to Download Google Sheets Connector for Azure Data Factory (Pipeline) and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).

Download Google Sheets Connector for Azure Data Factory (Pipeline) Documentation 

More integrations

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SQL Server

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Informatica

MS Access

MS Excel

SSAS

C#

Python

JAVA

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Talend Studio

UiPath

PowerShell

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Google BigQuery

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Google Drive

Google Sheets

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Jira

Mailchimp

ManagedEngine ServiceDesk Plus (Zoho)

Nativo

OData

OneDrive

Outlook Mail (Office 365)

Power BI

ServiceNow

SharePoint Online

Shopify

Smartsheet

Stripe

YouTube

Zendesk

Zoho CRM

Zoho SalesIQ

Zoom

REST API

JSON

JSON File

XML

SOAP

XML File

JDBC-ODBC Bridge

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CSV

Amazon S3 JSON File

Amazon S3 XML File

Amazon S3 CSV File

Azure Blob JSON File

Azure Blob XML File

Azure Blob CSV File

FTP/SFTP JSON File

FTP/SFTP XML File

FTP/SFTP CSV File

Build your own Custom API Connector

Download Google Sheets Connector for Azure Data Factory (Pipeline) Documentation

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