Power BI Connector for UiPath In this article you will learn how to integrate Power BI data in UiPath without coding in just a few clicks (live / bi-directional connection to Power BI). Connect to your Power BI account and retrieve data, refresh datasets, etc.. Using Power BI Connector you will be able to connect, read, and write data from within UiPath. 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 Power BI in other apps Connect to Power BI in SSIS Connect to Power BI in SQL Server Connect to Power BI in Power BI Connect to Power BI in SSRS Connect to Power BI in Informatica Connect to Power BI in MS Access Connect to Power BI in MS Excel Connect to Power BI in SSAS Connect to Power BI in C# Connect to Power BI in Python Connect to Power BI in JAVA Connect to Power BI in Tableau Connect to Power BI in SAP Crystal Reports Connect to Power BI in Azure Data Factory (Pipeline) Connect to Power BI in Azure Data Factory (SSIS) Connect to Power BI in Talend Studio Connect to Power BI in PowerShell Connect to Power BI in ODBC

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

Step-by-step instructions

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

1. Install ZappySys ODBC PowerPack.

2. Open ODBC Data Sources (x64):
   

3. Create a User Data Source (User 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.

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

   PowerBiDSN

   Power BI

   

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 Credentials [OAuth]

   OAuth App must be created in Microsoft Azure AD. These settings typically found here https://docs.microsoft.com/en-us/graph/auth-register-app-v2. [API Help..]

   Steps to get Power BI Credentials : User Credentials [OAuth]
   

   Firstly, login into Azure Portal and there create an OAuth application:

   1. Go to Azure Portal and login there.
   2. Then go to Azure Active Directory.
   3. On the left side click menu item App registrations
   4. Then proceed with clicking New registration.
   5. Enter a name for your application.
   6. Select the account types to support with the Supported account types option.
   7. In Redirect URI, select Web.
   8. In the textbox enter https://zappysys.com/oauth as the Redirect URI or another valid redirect URL.
   9. Use this same Redirect URI in the Redirect URI (must match App Redirect URL) grid row.
   10. Copy Client ID and paste it into the API Connection Manager configuration grid in the Client ID row.
   11. Click on the Endpoints link and copy the OAuth 2.0 authorization endpoint (v2) URL to the Authorization URL grid row. Usually it looks similar to this:
       • https://login.microsoftonline.com/daed1250-xxxx-xxxx-xxxx-ef0a982d3d1e/oauth2/v2.0/authorize
   12. Copy the OAuth 2.0 token endpoint (v2) URL to the Token URL grid row. Usually it looks similar to this:
       • https://login.microsoftonline.com/daed1250-xxxx-xxxx-xxxx-ef0a982d3d1e/oauth2/v2.0/token
   13. Close "Endpoints" popup and create a Client Secret in the Certificates & secrets tab.
   14. Proceed by clicking New client secret and setting expiration period. Copy the client secret and paste it into configuration grid in Client Secret row.
   15. Now lets setup permissions for the app. Click on API Permissions and on the page click Plus Sign Add Permission
   16. Click on Microsoft Graph API and then choose Delegated Permissions
   17. on Permission list page search or choose permissions as needed. We need to enable following Permissions from 2 Sections: Microsoft Graph API and Power BI Service.
   18. Make sure you have checked below permissions (If you do not need Write feature then you can skip Write scopes)

       offline_access
       Dataset.ReadWrite.All
       

   19. Click Generate Token to generate tokens.
   20. That's it!

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

   PowerBiDSN

   Power BI

   User Credentials [OAuth]

   https://api.powerbi.com/v1.0/myorg

   Required Parameters
   Authorization URL	Fill in the parameter...
   Token URL	Fill in the parameter...
   Client ID	Fill in the parameter...
   Scope	Fill in the parameter...
   Default DatasetId (select after generating tokens)	Fill in the parameter...
   Optional Parameters
   Client Secret	Fill in the parameter...
   Redirect URI (must match App Redirect URI)	Fill in the parameter...
   Default WorkspaceId (select after generating tokens)	Fill in the parameter...
   RetryMode	Fill in the parameter...
   RetryStatusCodeList	Fill in the parameter...
   RetryCountMax	Fill in the parameter...
   RetryWaitTimeMs	Fill in the parameter...
   RetryMultiplyWaitTime	Fill in the parameter...
   Login options	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 Power BI data in UiPath Studio (workstation)

Here we will be reading Power BI data on your workstation. To accomplish that we will create and run UiPath process package locally. Later on, we'll explore how to publish the package to Orchestrator and run it remotely. For now, let's focus on working locally and get started!

1. Open UiPath Studio.
2. Before we really begin the work, make sure UiPath Studio is set as your profile (blue application icon).
3. In case, it is set to UiPath StudioX, you can change it in UiPath StudioX Settings: Simply select UiPath Studio option:
4. Start by creating a new project based on UiPath Process template:
5. Add Run Query activity in Main Sequence box:
6. Click Configure Connection... button to create an ODBC connection:
7. Continue by clicking Connection Wizard:
8. When the window opens, select ODBC-based driver, provider, and then choose ODBC data source:
   PowerBiDSN

   PowerBiDSN

   
   You can also select Use connection string option and use whole ODBC connection string instead. Obtain the connection string by pressing Copy Settings button in your data source configuration.
9. Once you do that, it's time to configure a SQL query:
   Make sure, you enclose the query in double quotes!
10. Proceed by adding a Write CSV activity after Run Query:
    In this article we are using Write CSV, but you can freely add any other destination of your choice, e.g. Write DataTable to Excel.
11. Once you do that, configure the added Write CSV, this will write Power BI data to a CSV file:
12. It's time for fun! Which means it's time for debugging! Just run the package locally to debug:
13. Finally, ensure there are no execution errors!

Run UiPath package using Orchestrator (via robot)

UiPath also offers the ability to execute packages remotely using Orchestrator and a robot. This is achieved by publishing the package to UiPath Orchestrator, installing UiPath Assistant on the remote machine, connecting it to Orchestrator, enabling us to run the package remotely. It may sound complicated at first glance, but further steps will clear things out. Let's not waste our precious time and delve into the details!

Publish process package from UiPath Studio

1. First of all, open the UiPath process package we created in the previous step
2. Set the option that our process package Starts in Background:
3. We are ready to Publish it:
4. Make sure, you publish it to the Shared folder in UiPath Orchestrator Tenant workspace:
5. Finally, success! We are ready for the next step - creating UiPath robot - so we can automate the job:

Create robot in UiPath Orchestrator

1. First of all, let's open UiPath Orchestrator from UiPath Automation Cloud console:
2. It's time to create a robot, which will run unattended packages:
3. But first we have to create a runtime. Choose to host our robot on-premise, not in UiPath infrastructure:
4. Let's move along and Create new machine template, this will create a machine in UiPath Orchestrator:
5. Configure the machine to run in Production environment:
6. We are ready to Create new robot account in the new machine:
7. Let's make our robot to work only on background automations:
8. Continue by selecting newly created robot:
9. Select Shared folder, so that everyone in the team can benefit from it:
   This is the folder where we published our UiPath process package "MyProcess"
10. We are almost done! We are given machine Client ID and Client secret which we will use to connect UiPath Assistant to our created machine in Orchestrator. Let's leave this open for a while and see how we can do it in the next step.

Connect UiPath Assistant to Orchestrator

We are ready to connect UiPath Assistant to the machine we created in Orchestrator. UiPath Assistant will run our package in a remote machine. Let's connect it and give it some work!

1. Connect to a remote machine (where your UiPath process package will be running).
2. Install UiPath Studio there.
3. Then configure ODBC data source:

   If you chose Use user or system data source option in connection configuration, when creating UiPath process package, then create an identical ODBC data source on the same remote machine. Use the same configuration as the one created in your workstation in the first step.

   Use Copy Settings and Load Settings buttons to make your life easier. They will help you to transfer settings between different ODBC data sources.

   If you chose Use connection string option, then you don't have to do anything. However, you still have to install ODBC PowerPack on the remote machine.

4. Continue by opening UiPath Assistant and going to Preferences:
5. Find Orchestrator Settings menu item and click it:
6. And here even bigger fun begins! But fear not, all you have to do is open your web browser window with Client ID & Client secret we obtained in the previous step and simply copy and paste those values into UiPath Assistant. Also, don't forget to configure Orchestrator URL:
7. Finally, we get rewarded for the hard work with the Connected as Unattended status:

Create and run UiPath process in Orchestrator

We are at the finish line! Let's create and run UiPath process. This will execute the package on your remote machine using the UiPath Assistant configured earlier.

1. First of all, open UiPath Orchestrator from UiPath Automation Cloud console.
2. Then proceed by going to Process in Shared folder:
3. Continue by simply clicking on Add process button:
4. Select the process package we created in UiPath Studio:
5. Rest a while, and just hit Next, unless your package has requirements:
6. Then simply hit Create button:
7. But let's not stop here and Start the process by creating a job right away:
8. Use the same Production runtime we created before and hit Start:
9. We've reached the final step! In the CSV destination file or destination of your choice you should see Power BI data:

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 Power BI Connector

Power BI Connector Examples for UiPath 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 Workspaces

SELECT * 
FROM Workspaces
WHERE Id='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'

SELECT * 
FROM Datasets

SELECT * 
FROM Datasets
WITH (WorkspaceId = 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT * 
FROM Datasets
WHERE Id='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'

SELECT * 
FROM create_push_dataset
WITH (Definition='{
  "name": "My Push Dataset Name",
  "defaultMode": "Push",
  "tables": [
	{
      "name": "Products",
      "columns": [
        {
          "name": "Id",
          "dataType": "Int64"
        },
        {
          "name": "Name",
          "dataType": "string"
        },
        {
          "name": "Category",
          "dataType": "string"
        },
        {
          "name": "IsComplete",
          "dataType": "bool"
        },
        {
          "name": "ManufacturedOn",
          "dataType": "DateTime"
        },
        {
          "name": "Sales",
          "dataType": "Int64",
          "formatString": "Currency"
        },        
        {
          "name": "Price",
          "dataType": "Double",
          "formatString": "Currency"
        }
      ]
    }
  ]
}'
)

-- More info on creating a Push Dataset:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/push-datasets/datasets-post-dataset

SELECT * 
FROM create_push_dataset
WITH (Definition='{
  "name": "My Push Dataset Name",
  "defaultMode": "Push",
  "tables": [
     {
      "name": "Customers",
      "columns": [
        {
          "name": "Id",
          "dataType": "Int64"
        },
        {
          "name": "Name",
          "dataType": "string"
        }
      ]
    },
	{
      "name": "Products",
      "columns": [
        {
          "name": "Id",
          "dataType": "Int64"
        },
        {
          "name": "Name",
          "dataType": "string"
        },
        {
          "name": "Category",
          "dataType": "string"
        },
        {
          "name": "IsComplete",
          "dataType": "bool"
        },
        {
          "name": "ManufacturedOn",
          "dataType": "DateTime"
        },
        {
          "name": "Sales",
          "dataType": "Int64",
          "formatString": "Currency"
        },        
        {
          "name": "Price",
          "dataType": "Double",
          "formatString": "Currency"
        }
      ]
    }
  ]
}'
)

-- More info on creating a Push Dataset:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/push-datasets/datasets-post-dataset

SELECT *
FROM delete_dataset
WHERE Id = 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'

-- More info on deleting a Dataset:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/datasets/delete-dataset

SELECT *
FROM refresh_dataset
WHERE Id = 'aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee'
                
-- More info on refreshing a Dataset:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/datasets/refresh-dataset

SELECT * 
FROM get_tables

SELECT * 
FROM get_tables
WITH (DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT * 
FROM get_table_columns
WITH (TableName='MyTable')

SELECT * 
FROM get_table_columns
WITH (TableName='MyTable',
      DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT * 
FROM MyTable

SELECT *
FROM get_table_rows
WITH(
	  "TableName"='Products'
	, "DatasetId"='11b6c287-51d3-4061-bed8-811a4e5f6ce9'
	, "WorkspaceId"='848353e2-f3b1-4fb4-89d7-44e84b8bdf9f'
)

INSERT INTO Products 
SOURCE(
  'MSSQL',
  'Data Source=localhost\developer;Initial Catalog=Northwind;Integrated Security=true',
  '  SELECT T.* FROM (       SELECT  TOP 50                
      ProductName AS [Name]              
      ,C.CategoryName AS Category              
      ,Discontinued AS IsComplete              
      ,GETDATE() AS ManufacturedOn              
      ,CAST(UnitPrice * ReOrderLevel * 100 AS BIGINT) AS Sales              
      ,CAST(UnitPrice AS DECIMAL) AS Price       
      FROM Northwind.dbo.Products AS P       
      JOIN Northwind.dbo.Categories C ON P.CategoryId = P.CategoryId       
      ) AS T              
      CROSS JOIN GENERATE_SERIES(1, 2000)             
      -- COMMENT:  50 x 2000 = 100 000 rows  
   '
) 
CONNECTION(
  Parameters = '[{ Name: "TokenUrl",Value:"https://login.microsoftonline.com/organizations/oauth2/v2.0/token"}                         
  ,{ Name: "DatasetId",Value: "6a0e04da-a6e4-4533-abe4-30fcabd0e2a5"},                      
  { Name: "WorkspaceId",Value: "848353e2-f3b1-4fb4-89d7-44e84b8bdf9f"}]'
)

INSERT INTO MyTable(MyColumn1, MyColumn2, MyColumn3, MyColumn4, MyColumn5)
VALUES (1001, 'Glass', true, '2001-02-03', 195.95)

INSERT INTO MyTable(MyColumn1, MyColumn2, MyColumn3, MyColumn4, MyColumn5)
VALUES (1001, 'Glass', true, '2001-02-03', 195.95)
WITH (DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT * 
FROM get_table_rows 
WITH (TableName='MyTable')

SELECT * 
FROM get_table_rows 
WITH (TableName='MyTable', DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee')

SELECT *
FROM truncate_push_dataset_table
WITH (TableName='MyTable')
                
-- More info on truncating a Push Dataset Table:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/push-datasets/datasets-delete-rows

SELECT *
FROM truncate_push_dataset_table
WITH (DatasetId='aaaaaaaa-bbbb-cccc-dddd-eeeeeeeeeeee', TableName='MyTable')
                
-- More info on truncating a Push Dataset Table:
-- https://learn.microsoft.com/en-us/rest/api/power-bi/push-datasets/datasets-delete-rows

SELECT * 
FROM execute_dax_query
WITH (Query='EVALUATE ''MyTable''')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/filter-functions-dax
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query 
WITH (Query='EVALUATE FILTER(''MyTable'', [MyColumn] = "MyValue"')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://dax.guide/filter/
-- https://dax.guide/operators/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query 
WITH (Query='EVALUATE FILTER(''MyTable'', [MyColumn1] = "MyValue" && ([MyColumn2] > 0 || [MyColumn3] <= 1000))')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/operators/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query
WITH (Query='EVALUATE 
             SELECTCOLUMNS (
                ''MyTable'',
                "MyColumn1 alias", [MyColumn1],
                "MyColumn2 alias", [MyColumn2]
             )
             ORDER BY "MyColumn2 alias"'
    )
    
-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://dax.guide/selectcolumns/   
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query
WITH (Query='EVALUATE 
             TOPN(1000, ''MyTable'', [MyColumnOrExpression], ASC)')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://dax.guide/topn/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM execute_dax_query
WITH (Query='
DEFINE
    VAR MinimumAmount = 2000000
    VAR MaximumAmount = 8000000
EVALUATE
FILTER (
    ADDCOLUMNS (
        SUMMARIZE (Sales, Products[Category]),
        "CategoryAmount", [Sales Amount]
    ),
    AND (
        [CategoryAmount] <= MinimumAmount,
        [CategoryAmount] >= MaximumAmount
    )
)
ORDER BY [CategoryAmount]"')

-- More info on 'EVALUATE' statement and DAX queries:
-- https://dax.guide/st/evaluate/
-- https://dax.guide/addcolumns/
-- https://dax.guide/summarize/
-- https://dax.guide/st/order-by/
-- https://learn.microsoft.com/en-us/dax/dax-queries
-- https://learn.microsoft.com/en-us/dax/filter-functions-dax
-- https://learn.microsoft.com/en-us/dax/dax-syntax-reference

SELECT * 
FROM generic_request
WITH (Url='/groups',
Filter='$.value[*]')


/*
EXPLANATION:
- This configuration calls Power BI REST API "Get Groups" endpoint and gets the Workspaces back.
- This is achieved by "/groups" value in the "Url" parameter.
- The SQL query parameter "Filter" uses JsonPath "$.value[*]".
- This gets JSON objects from "value" array and transforms them into SQL rows.

MORE INFORMATION:
- About "Get Groups" REST API endpoint:
  https://learn.microsoft.com/en-us/rest/api/power-bi/groups/get-groups
- About JsonPath used in "Filter" parameter:
  https://zappysys.com/blog/jsonpath-examples-expression-cheetsheet  
*/

SELECT * 
FROM generic_request
WITH (Url='/groups?$filter=contains(name,''MyWorkspace'') or name eq ''My Blue Workspace''',
Filter='$.value[*]')


/*
EXPLANATION:
- This configuration calls Power BI REST API "Get Groups" endpoint and gets the Workspaces back.
- This is achieved by "/groups" value in the "Url" parameter.
- Workspaces are filtered on the Power BI REST API side by using the "$filter" URL parameter.
- Only those Workspaces are returned that:
  > contain a string value "MyWorkspace" or
  > if the Workspace name is "My Blue Workspace" (each single quote is escaped with two single quotes).
- The SQL query parameter "Filter" uses JsonPath "$.value[*]".
- This gets JSON objects from "value" array and transforms them into SQL rows.

MORE INFORMATION:
- About "Get Groups" REST API endpoint:
  https://learn.microsoft.com/en-us/rest/api/power-bi/groups/get-groups
- About JsonPath used in "Filter" parameter:
  https://zappysys.com/blog/jsonpath-examples-expression-cheetsheet  
*/

Conclusion

Download Power BI Connector for UiPath Documentation 

More integrations

Other application integration scenarios for Power BI

SSIS

SQL Server

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Informatica

MS Access

MS Excel

SSAS

C#

Python

JAVA

Tableau

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Azure Data Factory (Pipeline)

Azure Data Factory (SSIS)

Talend Studio

PowerShell

ODBC

Other connectors for UiPath

Amazon Ads

Amazon MWS

Azure DevOps

Cosmos DB

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ElasticSearch

FastSpring

Google BigQuery

Google Calendar

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Hubspot

Jira

Mailchimp

ManagedEngine ServiceDesk Plus (Zoho)

Nativo

OData

OneDrive

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ServiceNow

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Shopify

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JDBC-ODBC Bridge

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Amazon S3 JSON File

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