Shopify Connector for Power BI Shopify Connector can be used to integrate Shopify REST API in your App / BI Tools. You can read/write data about Customers, Orders, OrderItems, Products and more. In this article you will learn how to quickly and efficiently integrate Shopify data in Power BI without coding. We will use high-performance Shopify Connector to easily connect to Shopify and then access the data inside Power BI. Let's follow the steps below to see how we can accomplish that! Download Documentation Shopify Connector for Power BI is based on ZappySys API Driver which is part of ODBC PowerPack. It is a collection of high-performance ODBC drivers that enable you to integrate data in SQL Server, SSIS, a programming language, or any other ODBC-compatible application. ODBC PowerPack supports various file formats, sources and destinations, including REST/SOAP API, SFTP/FTP, storage services, and plain files, to mention a few.

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

Video Tutorial - Integrate Shopify data in Power BI

This video covers the following topics and more, so please watch carefully. After watching the video, follow the steps outlined in this article:

• How to download and install the required PowerPack for Shopify integration in Power BI
• How to configure the connection for Shopify
• Features of the ZappySys API Driver (Authentication / Query Language / Examples / Driver UI)
• How to use the Shopify in Power BI

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

Step-by-step instructions

To get data from Shopify using Power BI we first need to create a DSN (Data Source) which will access data from Shopify. We will later be able to read data using Power BI. Perform these steps:

1. Download and install ODBC PowerPack.

2. Open ODBC Data Sources (x64):

   

3. Create a User data source (User DSN) based on ZappySys API Driver

   ZappySys API Driver

   
   • Create and use User DSN if the client application is run under a User Account. This is an ideal option in design-time, when developing a solution, e.g. in Visual Studio 2019. Use it for both type of applications - 64-bit and 32-bit.
   • Create and use System DSN if the client application is launched under a System Account, e.g. as a Windows Service. Usually, this is an ideal option to use in a production environment. Use ODBC Data Source Administrator (32-bit), instead of 64-bit version, if Windows Service is a 32-bit application.
   Power BI uses a Service Account, when a solution is deployed to production environment, therefore for production environment you have to create and use a System DSN.

4. When the Configuration window appears give your data source a name if you haven't done that already, then select "Shopify" from the list of Popular Connectors. If "Shopify" 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:

   ShopifyDSN

   Shopify

   

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.

    Access Token [Http]

   Steps how to get and use Shopify credentials : Access Token [Http]
   Setting up your Shopify store account for API access involves creating an "app" for your store. The "app" is installed into the Shopify account and configured with the appropriate access levels for your data integration needs.

   1. Visit https://accounts.shopify.com and log into your Shopify store account.
   2. After logging in, select the store to connect to with the ZappySys Shopify Connector.
   3. Select the Settings link (usually in the lower-left corner) to launch the Settings screen.
   4. On the left menu panel, select Apps and sales channels.
   5. On the Apps and sales channels screen, select Develop apps (near the top of the screen).
   6. On the App development screen, select Create an app (near the upper-right corner of the screen).
   7. Give the app that will be used to provide Shopify API access a name, select the appropriate developer from the App developer drop-down, and then select Create app.
   8. Select Configure Admin API scopes and the Admin API access scopes screen will appear.
   9. In the Admin API access scopes screen, select every access scope checkbox that applies to your integration needs. It is generally not a good idea to allow more access than what is needed in order to fulfill your integration needs.
      • To enable the reading of customer information, select read_customers.
      • To enable the writing of customer information, select write_customers.
      • To enable the reading of inventory item information, select read_inventory.
      • To enable the writing of inventory item information, select write_inventory.
      • To enable the reading of order information, select read_orders.
      • To enable the writing of order information, select write_orders.
      After selecting all applicable access scopes, select Save.
   10. Install the app by selecting the Install app button (near the upper-right corner of the screen). If any other prompts for installation appears, select Install.
   11. After the app is installed, the Admin API access token will be available in the API credentials tab of the page. It can only be revealed ONCE for security purposes. Select Reveal token once to show the new Admin API access token. SAVE THE ADMIN API ACCESS TOKEN IN A SAFE PLACE WHERE YOU HAVE IT CONFIDENTIAL, SECURE, AND NOT ACCESSIBLE TO UNAUTHORIZED INDIVIDUALS. The Admin API access token will be needed in this process later.
   12. In the ZappySys connector API screen, enter the subdomain of your Shopify store into the Subdomain parameter textbox. For example, if your Shopify URL is https://acmetoys.myshopify.com, the subdomain would be acmetoys.
   13. In the same screen, enter the Admin API access token saved from step 11 above into the Admin API Access Token textbox. In order to edit the text in this field, select the ellipses (...) button that appears when the textbox is clicked and edit the access token with the dialog box that appears.
   14. Select the Test Connection button at the bottom of the window to verify proper connectivity with the Shopify store.
   15. If the connection test succeeds, select OK.

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

   ShopifyDSN

   Shopify

   Access Token [Http]

   https://[$Subdomain$].myshopify.com/admin/api/2023-01

   Required Parameters
   Sub-domain	Fill-in the parameter...
   Admin API Access Token	Fill-in the parameter...
   Optional Parameters
   RetryMode	RetryWhenStatusCodeMatch
   RetryStatusCodeList	429
   RetryCountMax	5
   RetryMultiplyWaitTime	True

   

6. Once the data source connection has been configured, it's time to configure the SQL query. Select the Preview tab and then click Query Builder button to configure the SQL query:

   

   ZappySys API Driver - Shopify

   Shopify Connector can be used to integrate Shopify REST API in your App / BI Tools. You can read/write data about Customers, Orders, OrderItems, Products and more.

   ShopifyDSN

   

7. Start by selecting the Table or Endpoint you are interested in and then configure the parameters. This will generate a query that we will use in Power BI to retrieve data from Shopify. Hit OK button to use this query in the next step.

   SELECT * FROM Products

   
   Some parameters configured in this window will be passed to the Shopify API, e.g. filtering parameters. It means that filtering will be done on the server side (instead of the client side), enabling you to get only the meaningful data much faster.

8. Now hit Preview Data button to preview the data using the generated SQL query. If you are satisfied with the result, use this query in Power BI:

   

   ZappySys API Driver - Shopify

   Shopify Connector can be used to integrate Shopify REST API in your App / BI Tools. You can read/write data about Customers, Orders, OrderItems, Products and more.

   ShopifyDSN

   SELECT * FROM Products

   
   You can also access data quickly from the tables dropdown by selecting <Select table>.
   A WHERE clause, LIMIT keyword will be performed on the client side, meaning that the whole result set will be retrieved from the Shopify API first, and only then the filtering will be applied to the data. If possible, it is recommended to use parameters in Query Builder to filter the data on the server side (in Shopify servers).

9. Click OK to finish creating the data source.

Video Tutorial

Read Shopify data in Power BI using ODBC

Importing Shopify data into Power BI from table or view

1. Once you open Power BI Desktop click Get Data to get data from ODBC:
   

2. A window opens, and then search for "odbc" to get data from ODBC data source:
   

3. Another window opens and asks to select a Data Source we already created. Choose ShopifyDSN and continue:

   ShopifyDSN

   

4. Most likely, you will be asked to authenticate to a newly created DSN. Just select Windows authentication option together with Use my current credentials option:

   ShopifyDSN

   

5. Finally, you will be asked to select a table or view to get data from. Select one and load the data!
   

6. Finally, finally, use extracted data from Shopify in a Power BI report:
   

Importing Shopify data into Power BI using SQL query

If you wish to import Shopify data from SQL query rather than a table then you can use advanced options during import steps (as below). After selecting DSN you can click on advanced options to see SQL Query editor.

ShopifyDSN

SELECT * FROM Products

Using a full ODBC connection string

In the previous steps we used a very short format of ODBC connection string - a DSN. Yet sometimes you don't want a dependency on an ODBC data source (and an extra step). In those times, you can define a full connection string and skip creating an ODBC data source entirely. Let's see below how to accomplish that in the below steps:

1. Open ODBC data source configuration and click Copy settings:
   

   ZappySys API Driver - Shopify

   Shopify Connector can be used to integrate Shopify REST API in your App / BI Tools. You can read/write data about Customers, Orders, OrderItems, Products and more.

   ShopifyDSN

   
2. The window opens, telling us the connection string was successfully copied to the clipboard:
3. Then just paste the connection string into your script:
   ShopifyDSN

   DRIVER={ZappySys API Driver};ServiceUrl=https://[$Subdomain$].myshopify.com/admin/api/2023-01;CredentialType=Token;AuthScheme={none};TokenAuthHeader=X-Shopify-Access-Token;

   
4. You are good to go! The script will execute the same way as using a DSN.

Limitations of using a full connection string

Despite using a full ODBC connection string may be very convenient it comes with a limitation: it's length is limited to 1024 symbols (or sometimes more). It usually happens when API provider generates a very long Refresh Token when OAuth is at play. If you are using such a long ODBC connection string, you may get this error:

"Connection string exceeds maximum allowed length of 1024"

But there is a solution to this by storing the full connection string in a file. Follow the steps below to achieve this:

1. Open your ODBC data source.
2. Click Copy settings button to copy a full connection string (see the previous section on how to accomplish that).
3. Then create a new file, let's say, in C:\temp\odbc-connection-string.txt.
4. Continue by pasting the copied connection string into a newly created file and save it.
5. Finally, the last step! Just construct a shorter ODBC connection string using this format:

   DRIVER={ZappySys API Driver};SettingsFile=C:\temp\odbc-connection-string.txt

6. Our troubles are over! Now you should be able to use this connection string in Power BI with no problems.

Editing query for table in Power BI

There will be a time you need to change the initial query after importing data into Power BI. Don't worry, just right-click on your table and click Edit query menu item:

Using parameters in Power BI (dynamic query)

In the real world, many values of your REST / SOAP API call may be coming from parameters. If that's the case for you can try to edit script manually as below. In below example its calling SQL Query with POST method and passing some parameters. Notice below where paraAPIKey is Power BI Parameter (string type). You can use parameters anywhere in your script just like the normal variable.

To use a parameter in Power BI report, follow these simple steps:

1. Firstly, you need to Edit query of your table (see previous section)

2. Then just create a new parameter by clicking Manage Parameters dropdown, click New Parameter option, and use it in the query:

   						
                               = Odbc.Query("dsn=ShopifyDSN",
                                            "SELECT ProductID, ProductName, UnitPrice, UnitsInStock
                                             FROM Products
                                             WHERE UnitPrice > " & Text.From(MyParameter) & "
                                             ORDER BY UnitPrice")
                           
                   

   
   Refer to Power Query M reference for more information on how to use its advanced features in your queries.

Using DirectQuery Option rather than Import

So far we have seen how to Import Shopify data into Power BI, but what if you have too much data and you don't want to import but link it. Power BI Offers very useful feature for this scenario. It's called DirectQuery Option. In this section we will explore how to use DirectQuery along with ZappySys Drivers.

Out of the box ZappySys Drivers won't work in ODBC Connection Mode, so you have to use SQL Server Connection rather than ODBC if you wish to use Live data using DirectQuery option. See below step-by-step instructions to enable DirectQuery mode in Power BI for Shopify data.

Basically we will use ZappySys Data Gateway its part of ODBC PowerPack. We will then use Linked Server in SQL Server to Link API Service, then issue OPENROWSET queries from Power BI to SQL Server, and it will then call Shopify via ZappySys Data Gateway.

1. First, create a data source in ZappySys Data Gateway and create a Linked Server based on it.
2. Once SQL Server Linked Server is configured we are ready to issue a SQL query in Power BI.
3. Click Get Data in Power BI, select SQL Server Database
4. Enter your server name and any database name
5. Select Mode as DirectQuery
6. Click on Advanced and enter query like below (we are assuming you have created Shopify Data Source in Data Gateway and defined linked server - change the name below).

   SELECT * FROM OPENQUERY([LS_TO_SHOPIFY_IN_GATEWAY], 'SELECT * FROM Products')

   SELECT * FROM OPENQUERY([LS_TO_SHOPIFY_IN_GATEWAY], 'SELECT * FROM Products')

   

   
   DirectQuery option for Power BI (Read Shopify Data Example using SQL Server Linked Server and ZappySys Data Gateway)

7. Click OK and Load data... That's it. Now your Shopify API data is linked rather than imported.

Publishing Power BI report to Power BI service

Here are the instructions on how to publish a Power BI report to Power BI service from Power BI Desktop application:

1. First of all, go to Power BI Desktop, open a Power BI report, and click Publish button:

   

2. Then select the Workspace you want to publish report to and hit Select button:

   

3. Finally, if everything went right, you will see a window indicating success:

   

   If you need to periodically refresh Power BI semantic model (dataset) to ensure data accuracy and up-to-dateness, you can accomplish that by using Microsoft On-premises data gateway. Proceed to the next section - Refreshing Power BI semantic model (dataset) using On-premises data gateway - and learn how to do that.

Refreshing Power BI semantic model (dataset) using On-premises data gateway

Power BI allows to refresh semantic models which are based on data sources that reside on-premises. This can be achieved using Microsoft On-premises data gateway. There are two types of On-premises gateways:

• Standard Mode
• Personal Mode

Standard Mode supports Power BI and other Microsoft Data Fabric services. It fits perfectly for Enterprise solutions as it installs as a Windows Service and also supports Direct Query feature.

Personal Mode, on the other hand, can be configured faster, but is designed more for home users (you cannot install it as a Windows Service and it does not support DirectQuery). You will find a detailed comparison in the link above.

We recommend to go with Personal Mode for a quick POC solution, but use Standard Mode in production environment.

Below you will find instructions on how to refresh semantic model using both types of gateways.

Refresh using On-premises data gateway (standard mode)

Here are the instructions on how to refresh a Power BI semantic model using On-premises data gateway (standard mode):

1. Go to Power BI My workspace, hover your mouse cursor on your semantic model and click Settings:

   

2. If you see this view, it means you have to install On-premises data gateway (standard mode):

   

3. Install On-premises data gateway (standard mode) and sign-in:

   
   Use the same email address you use when logging in into Power BI account.

4. Register a new gateway (or migrate an existing one):

   

5. If you are creating a new gateway, name your gateway, enter a Recovery key, and click Configure button:

   

6. Now, let's get back to your semantic model settings in Power BI portal. Refresh the page and you should see your newly created gateway. Click arrow icon and then click on Add to gateway link:

   ODBC{"connectionstring":"dsn=ShopifyDSN"}

   

7. Once you do that, you will create a new gateway connection. Give it a name, set Authentication method, Privacy level, and click Create button:

   dsn=ShopifyDSN

   
   In this example, we used the least restrictive Privacy level.

   If your connection uses a full connection string you may hit a length limitation when entering it into the field. To create the connection, you will need to shorten it manually. Check the section about the limitation of a full connection string on how to accomplish it.

   On-premises data gateway (personal mode) does not have this limitation.

8. Proceed by choosing the newly created connection:

   ODBC{"connectionstring":"dsn=ShopifyDSN"}

   

9. Finally, you are at the final step where you can refresh the semantic model:

   

Refresh using On-premises data gateway (personal mode)

Here are the instructions on how to refresh a Power BI semantic model using On-premises data gateway (personal mode):

1. Go to Power BI My workspace, hover your mouse cursor on your semantic model and click Settings:

   

2. If you see this view, it means you have to install On-premises data gateway (personal mode):

   

3. Install On-premises data gateway (personal mode) and sign-in:

   
   Use the same email address you use when logging in into Power BI account.

4. Again, go to your semantic model Settings, expand Data source credentials, click Edit credentials, select Authentication method together with Privacy level, and then click Sign in button:

   dsn=ShopifyDSN

   

5. Finally, you are ready to refresh your semantic model:

   

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([LS_TO_SHOPIFY_IN_GATEWAY], '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([LS_TO_SHOPIFY_IN_GATEWAY], '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 Shopify Connector

Shopify Connector Examples for Power BI 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 Products

SELECT * FROM Products WITH Id=1111111111111

SELECT * FROM Products WITH(ids='1111111111111,2222222222222,3333333333333')

INSERT INTO Products 
(
	 Title
	,Status
	,BodyHtml
	,UrlHandle
	,Vendor
	,ProductType
	,Variants
	,Options
	,Tags
	,Metafields
	,Images	
	)
VALUES	
('Ice Cream'
,'draft'
,'<strong>Very yummy ice cream!</strong>'
,'ice-cream' 
,'Burton'
,'Snowboard' 

,'[
	{"price":10.5, "option1":"Chocolate","option2":"Small","sku":"ICE-CHO-SML","inventory_quantity":100},
	{"price":10.5, "option1":"Chocolate","option2":"Medium","sku":"ICE-CHO-MED","inventory_quantity":100},
	{"price":11.5, "option1":"Vanilla","option2":"Small","sku":"ICE-VNL-MED","inventory_quantity":210}
  ]'

--you must set variants and use atlease one value from the below list in option1, option2 or option3 in any variant entry else it will fail.  
,'[
	{"name":"Color","values":["Chocolate","Vanilla"]}, 
	{"name":"Size","values":["Small","Medium"]}
  ]' 

,'["Frozen","Seasonal","Dad''s Fav"]'

--adding metadata (custom fields) - metadata fields must be created before setting it 
--below are 2 system fields for SEO Title / SEO Description (you dont need to create them unlike custom metadata). These values appears on SEO section
,'[
	{"key":"title_tag","value":"Yum Ice Cream SEO Title", "namespace":"global","type":"single_line_text_field"}, 
	{"key":"description_tag","value":"Yum Ice Cream SEO description", "namespace":"global","type":"single_line_text_field"} 
  ]'

--first image becomes main image if you supply multiple images 
--upload multiple images from URL (set "src")
 , '[	
	{"src":"https://zappysys.com/images/tech/google-analytics-logo.png"},
	{"src":"https://zappysys.com/images/tech/web-api-logo.png"}
  ]'
--OR upload multiple local image files (set "attachment")
--, '[	
--	 {"attachment":"<<c:\temp\icecream_1.png,FUN_FILE_BASE64ENC>>"},
--	 {"attachment":"<<c:\temp\icecream_2.png,FUN_FILE_BASE64ENC>>"}
--  ]'  
  
)

UPDATE Products
SET Title='Ice Cream - Updated'
 , Status='draft' --active, archived, draft  
 , BodyHtml='<strong>Very yummy ice cream - updated!</strong>'  
--first image becomes main image if you supply multiple images 
--upload multiple images from URL (set "src")
 , Images='[	
	{"src":"https://zappysys.com/images/tech/google-analytics-logo.png"},
	{"src":"https://zappysys.com/images/tech/web-api-logo.png"}
  ]'
--OR upload multiple local image files (set "attachment")
--, Images='[	
--	 {"attachment":"<<c:\temp\icecream_1.png,FUN_FILE_BASE64ENC>>"},
--	 {"attachment":"<<c:\temp\icecream_2.png,FUN_FILE_BASE64ENC>>"}
--  ]'

 , Variants='[
	{"price":20.5, "option1":"Chocolate","option2":"Small","sku":"ICE-CHO-SML","inventory_quantity":300},
	{"price":21.5, "option1":"Vanilla","option2":"Small","sku":"ICE-VNL-MED","inventory_quantity":110}
  ]'
, PublishedScope='global' --or web
, Vendor ='IceGlobal'
, ProductType ='Cold Food'
, Tags ='["Frozen","Seasonal","Dad''s Fav"]'
--Update SEO URL
 ,UrlHandle='ice-cream-51' 
--Update SEO title / description
, SEOTitle='Yum Ice Cream SEO Title-update'  
, SEODescription='Yum Ice Cream SEO description-update'  
Where Id=7348335771748

DELETE FROM Products
Where Id=7348335771748

SELECT * FROM ProductVariants

SELECT * FROM ProductVariants Where ProductId='1111111111111'

SELECT * FROM ProductVariants WITH(ids='1111111111111,2222222222222,3333333333333')

INSERT INTO ProductVariants (ProductId, Option1, Option2,SKU,Price,CompareAtPrice,Position,Weight,WeightUnit,ImageId)
Values(7348335771748, 'Chocolate', 'Medium', 'ICE-CHO-MED', 195.5, 200.5, 3, 20.5, 'lb', 31900013854820)

Update ProductVariants 
SET  
	,Option1='Chocolate' 
	,Option2='Large'
	,SKU='ICE-CHO-SML'
	,Price=90.45
	,CompareAtPrice=100.45
	,Position=2
	,Weight=10.5
	,WeightUnit='lb'
	,ImageId=31900013854820  --use available images from Products table
Where Id=42564507992164

DELETE FROM ProductVariants 
WHERE Id=31900013854820

SELECT * FROM Customers

SELECT * FROM Customers Where Id=12345

SELECT * FROM Customers
WITH (ids='1111111111111,2222222222222,3333333333333')

INSERT INTO Customers
(FirstName, LastName, Email, Phone, Password, PasswordConfirmation, SendWelcomeEmail, MultipassIdentifier, Note, Tags, TaxExempt, TaxExemptions, DefaultAddressFirstName, DefaultAddressLastName, DefaultAddressCompany, DefaultAddressLine1, DefaultAddressLine2, DefaultAddressCity, DefaultAddressProvince, DefaultAddressCountry, DefaultAddressZip, DefaultAddressPhone, DefaultAddressName, DefaultAddressProvinceCode, DefaultAddressCountryCode, DefaultAddressCountryName)
VALUES
('John', 'Doe', 'john.doe@gmail.com', '7705553543', 'myNewP@ssword123', 'myNewP@ssword123', 1, null, 'This is a note on the customer account.', null, 0, null, 'John', 'Doe', 'John Doe Corp.', '123 Main Street', null, 'Atlanta', 'Georgia', 'United States', '30135', '7705553543', 'John Doe', 'GA', 'US', 'United States')

INSERT INTO Customers(_rawdoc_)
VALUES('{"customer":{"first_name":"John","last_name":"Doe","email":"a.doe@gmail.com","phone":"7705553111"}}')

INSERT INTO Customers(FirstName, LastName, Email, Phone)
SOURCE('MSSQL'
  ,'Data Source=localhost;Initial Catalog=tempdb;Integrated Security=true'
  ,'select ''John'' as FirstName, ''Doe'' as LastName, ''a.doe@gmail.com'' as Email, ''7705553111'' as Phone'
)

INSERT INTO Customers
SOURCE('MSSQL'
	,'Data Source=localhost;Initial Catalog=tempdb;Integrated Security=true'
	,'select ''{"customer":{"first_name":"Cust1","last_name":"Doe1","email":"a.doe@gmail.com","phone":"7705553111"}}'' as _rawdoc_
	 UNION 
	 select ''{"customer":{"first_name":"Cust2","last_name":"Doe2","email":"b.doe@gmail.com","phone":"7705553222"}}'' as _rawdoc_
	 '
	)

UPDATE Customers SET
  Email = 'john.doe2@gmail.com',
  Phone = '7705553445',
  Note= 'This is a new note that needed to be added later.'
  WHERE Id=1111111111111

UPDATE Customers
SET _rawdoc_='{"customer":{"first_name":"John_new","last_name":"Doe_new","email":"a_new.doe@gmail.com","phone":"7705553111"}}'
WHERE Id=1111111111111

UPDATE Orders SET
  FulfillmentStatus = 'john.doe5@gmail.com',
  Phone = '7705553111',
  Note= 'This is a new note that needed to be added to the order later.'
WHERE Id=1111111111111

UPDATE Customers
SOURCE('MSSQL'
 ,'Data Source=localhost;Initial Catalog=tempdb;Integrated Security=true'
 ,'select 111 as Id, ''a@a.com''Email , ''SOLD'' as Note,0 as [$$ContineOn404Error]
  UNION
  select 222 as Id, ''b@b.com''Email , ''SOLD'' as Note,0 as [$$ContineOn404Error]
  '
)

DELETE Customers WHERE Id=1111111111111

DELETE Customers WHERE Id=1111111111111 (ContineOn404Error=0)

DELETE FROM Customers
SOURCE('MSSQL'
  ,'Data Source=localhost;Initial Catalog=tempdb;Integrated Security=true'
  ,'select 111 as Id,1 as [$$ContineOn404Error]
    UNION
    select 222 as Id,1 as [$$ContineOn404Error]
   '
)

SELECT * FROM Orders

SELECT * FROM Orders WITH (Status='open') --also try 'any', 'open', 'closed', 'cancelled'

SELECT * FROM Orders Where Id=1111111111111

SELECT * FROM Orders WITH(ids='1111111111111,2222222222222,3333333333333')

DELETE Orders WHERE Id=1111111111111

DELETE Orders WHERE Id=1111111111111 (ContineOn404Error=0)

SELECT * FROM OrderItems

SELECT * FROM OrderItems Where OrderId=1111111111111

SELECT * FROM OrderItems WITH(ids='1111111111111,2222222222222,3333333333333')

INSERT INTO Orders (BillingAddressLine1, BillingAddressLine2, BillingAddressCity, BillingAddressCompany, BillingAddressCountry, BillingAddressFirstName, BillingAddressLastName, BillingAddressPhone, BillingAddressProvince, BillingAddressZip, BillingAddressName, BillingAddressProvinceCode, BillingAddressCountryCode, BuyerAcceptsMarketing, LineItems, CustomerId, Email, EstimatedTaxes, FinancialStatus, FulfillmentStatus, Name, Note, Phone, Currency, PresentmentCurrency, ProcessedAt, ReferringSite, ShippingAddressLine1, ShippingAddressLine2, ShippingAddressCity, ShippingAddressCompany, ShippingAddressCountry, ShippingAddressFirstName, ShippingAddressLastName, ShippingAddressPhone, ShippingAddressProvince, ShippingAddressZip, ShippingAddressName, ShippingAddressProvinceCode, ShippingAddressCountryCode, Tags, TaxesIncluded, TotalWeight, SendReceipt, SendFulfillmentReceipt)
VALUES
('123 Main Street', 'Suite #54', 'Memphis', 'Acme, Inc.', 'United States', 'John', 'Doe', '4045559876', 'Tennessee', '38101', 'John Doe', 'GA', 'US', 1, '[{"title":"Super Strong Glue","price":24.99,"grams":"100","quantity":1,"tax_lines":[{"price":13.5,"rate":0.06,"title":"State tax"}]}]', 5945175474276, 'johndoe2@gmail.com', 1, 'pending', null, '#40294', 'This order needs to be expedited, so register it in the system as so.', '4045559876', 'USD', 'USD', '2023-02-27T11:00:00', 'https://referringsite.com', '123 Main Street', 'Suite #54', 'Memphis', 'Acme, Inc.', 'United States', 'John', 'Doe', '4045559876', 'Tennessee', '38101', 'John Doe', 'GA', 'US', NULL, 1, 20, 1, 1)

select * from InventoryLevels 
		--WITH(location_ids='43512280416356, 44648752676964, ..... upto 300 to 500 more - until you hit URL limit error')

select * from InventoryLevels WITH (inventory_item_ids='43512280416356, 44648752676964')

select * from InventoryLevels WITH (location_ids='43512280416356, 44648752676964')

select * from InventoryLevels WITH (inventory_item_ids='43512280416356, 44648752676964' , location_ids='111100034, 111100055')

UPDATE InventoryLevels 
SET AvailableAdjustment=488, 
    LocationId=25801916516
WHERE InventoryItemId=43512276942948
WITH(
 Action='Adjust' --or set or connect
, ContineOn404Error=0 
)

UPDATE InventoryLevels 
SET LocationId=25801916516
  ,Available=488 
WHERE InventoryItemId=43512276942948
WITH(
 Action='set' --or adjust or connect
, ContineOn404Error=0 
)

--OR--
/*
INSERT INTO InventoryLevels (InventoryItemId,LocationId,Available)
VALUES(43512276942948, 25801916516, 488)
--WITH( ContineOn404Error=0 )
*/

UPDATE InventoryLevels 
SET LocationId=25801916516
WHERE InventoryItemId=43512276942948
WITH(
 Action='connect' --or adjust or set
, ContineOn404Error=0 
)

SELECT * FROM generic_request 
WITH (
    URL='/inventory_levels/set.json'
  --OR Use full URL
  --URL='https://MY-STORE-HERE.myshopify.com/admin/api/2023-01/inventory_levels/set.json'
  	
  , RequestMethod='POST'
  , Body='{"location_id":25801916516,"inventory_item_id":43512280416356,"available":42}' --needed if you call PUT, POST
  , Filter='$.inventory_level' --change table name here
  , Headers='Content-Type: application/json'
  , Meta='inventory_item_id:long; location_id:long; available:int; updated_at: datetime'
)

select * from InventoryItems Where Id=43512280416356

select * from InventoryItems Where Id=43512280416356

select * from InventoryItems WITH(Ids='43512280416356, 43512280449124')

UPDATE InventoryItems
SET Cost='25.55'
WHERE Id=43512280416356

SELECT * FROM generic_request 
WITH (
    URL='/graphql.json'
  --OR Use full URL
  --URL='https://MY-STORE-HERE.myshopify.com/admin/api/2023-10/graphql.json'
  
  , RequestMethod='POST'
  , Filter='$.data.products.nodes' --change table name here e.g. products
  , Headers='Content-Type: application/json'
  --change table name and columns below here e.g. products... and id, title etc
  -- change pagesize if needed (i.e. max 250)
  , Body='{
 "query" : "<<{
 
 products(first: 250 [$tag$])
 {
    nodes {
      id
      title
      createdAt
    }
    
    pageInfo {
      hasNextPage
      endCursor
    }
    
  }
  
},FUN_JSONENC>>"
}'
	, NextUrlAttributeOrExpr='$.data.products.pageInfo.endCursor' --change table name 
	, NextUrlEndIndicator='false'
	, StopIndicatorAttributeOrExpr='$.data.products.pageInfo.hasNextPage' --change table name 
	, UseConnection='True'
	, EnablePageTokenForBody='True'
	, HasDifferentNextPageInfo='True'
	, NextPageBodyPart='after: \"[$pagetoken$]\"'
	--Use metadata to speed up execution. To get Metadata Run query without Meta clause. 
	-- Then click View Metadata button found in Botttom Result Grid Toolbar. Get Compact format and paste below
	--, Meta='id:String(255); title:String(255); createdAt:DateTime; '
)

SELECT * FROM generic_request 
WITH (
    URL='/products.json'
  --OR Use full URL
  --URL='https://MY-STORE-HERE.myshopify.com/admin/api/2023-01/products.json'
  	
  , RequestMethod='GET'
  , Body='{}' --needed if you call PUT, POST
  , Filter='$.products[*]' --change table name here
  , Headers='Content-Type: application/json'
  , PagingMode='ByResponseHeaderRfc5988'
  
  
  --Use metadata to speed up execution. To get Metadata Run query without Meta clause. 
  --Then click View Metadata button found in Botttom Result Grid Toolbar. Get Compact format and paste below
  , Meta='id:String(255); title:String(255); created_at:DateTime; '
)

Conclusion

In this article we showed you how to connect to Shopify in Power BI and integrate data without any coding, saving you time and effort. It's worth noting that ZappySys API Driver allows you to connect not only to Shopify, but to any Java application that supports JDBC (just use a different JDBC driver and configure it appropriately).

We encourage you to download Shopify Connector for Power BI and see how easy it is to use it for yourself or your team.

If you have any questions, feel free to contact ZappySys support team. You can also open a live chat immediately by clicking on the chat icon below.

Download Shopify Connector for Power BI Documentation

More integrations

Other connectors for Power BI

Amazon Ads

Amazon Athena

Amazon Selling Partner (SP-API)

Apache Derby

Asana

Azure DevOps

Cosmos DB

DropBox

ElasticSearch

FastSpring

Google Ads

Google BigQuery

Google Calendar

Google Drive

Google Sheets

Hubspot

Infor Data Lake

Jira

Mailchimp

ManagedEngine ServiceDesk Plus (Zoho)

MariaDB

OData

OneDrive

Outlook Mail (Office 365)

Power BI

ServiceNow

SharePoint Online

Smartsheet

Starburst

Stripe

Trino

YouTube

Zendesk

Zoho CRM

Zoho SalesIQ

Zoom

REST API

JSON

JSON File

XML

SOAP

XML File

JDBC-ODBC Bridge

Salesforce

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

Other application integration scenarios for Shopify

SSIS

SQL Server

SSRS

Informatica

MS Access

MS Excel

SSAS

C#

Python

JAVA

Tableau

SAP Crystal Reports

Azure Data Factory (Pipeline)

Azure Data Factory (SSIS)

Talend Studio

UiPath

PowerShell

ODBC

Common Searches: