JSON Connector for Power BI

JSON Connector can be used to extract and output JSON data coming from REST API web service calls (Web URL) or direct JSON String (variables or DB columns) or local JSON files data. JSON Connector also supports JSONPath to filter data from nested array/sub-documents. This Connector is optimized to work with very large JSON string.

In this article you will learn how to quickly and efficiently integrate JSON data in Power BI without coding. We will use high-performance JSON Connector to easily connect to JSON and then access the data inside Power BI.

Let's follow the steps below to see how we can accomplish that!

Download Documentation

JSON Connector for Power BI is based on ZappySys JSON 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 JSON in other apps

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Connect to JSON in MS Access

Connect to JSON in MS Excel

Connect to JSON in SSAS

Connect to JSON in C#

Connect to JSON in Python

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Connect to JSON in SAP Crystal Reports

Connect to JSON in Azure Data Factory (Pipeline)

Connect to JSON in Azure Data Factory (SSIS)

Connect to JSON in Talend Studio

Connect to JSON in UiPath

Connect to JSON in PowerShell

Connect to JSON in ODBC

Video Tutorial - Integrate JSON 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 JSON integration in Power BI
How to configure the connection for JSON
Features of the ZappySys JSON Driver (Authentication / Query Language / Examples / Driver UI)
How to use the JSON in Power BI

Watch this video on YouTube

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

Step-by-step instructions

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

Download and install ODBC PowerPack.
Open ODBC Data Sources (x64):
Create a User data source (User DSN) based on ZappySys JSON Driver

ZappySys JSON 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.
Select Url or File and paste the following Url for this example OR you can load existing connection string as per this article.

NOTE: Here for demo, We are using odata API, but you need to refer your own API documentation and based on that you need to use your own API URL and need to configure connection based on API Authentication type

https://services.odata.org/V3/Northwind/Northwind.svc/Customers?$format=json
Now enter JSONPath expression in Array Filter textbox to extract only specific part of JSON file as below ($.value[*] will get content of value attribute from JSON document. Value attribute is array of JSON documents so we have to use [*] to indicate we want all records of that array)

NOTE: Here, We are using our desired filter, but you need to select your desired filter based on your requirement.

Click on Test Connection button to view whether the Test Connection is SUCCESSFUL or Not.

$.value[*]
Once you configured a data source, you can preview data. Hit Preview tab, and use similar settings to preview data:
Click OK to finish creating the data source
That's it; we are done. In a few clicks we configured the call to JSON API using ZappySys JSON Connector.

Video Tutorial

Watch this video on YouTube

Read JSON data in Power BI using ODBC

Importing JSON data into Power BI from table or view

Once you open Power BI Desktop click Get Data to get data from ODBC:
A window opens, and then search for "odbc" to get data from ODBC data source:
Another window opens and asks to select a Data Source we already created. Choose JsonDSN and continue:

JsonDSN
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:

JsonDSN
Finally, you will be asked to select a table or view to get data from. Select one and load the data!
Finally, finally, use extracted data from JSON in a Power BI report:

Importing JSON data into Power BI using SQL query

If you wish to import JSON 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.

JsonDSN

            SELECT
                ProductID,
                ProductName,
                SupplierID,
                CategoryID,
                QuantityPerUnit,
                UnitPrice
            FROM _root_
            WHERE UnitPrice > 20

Get REST API data in Power BI Desktop using SQL query and ODBC

Consider using Custom Objects feature in ODBC data source to encapsulate SQL query in a Virtual Table. This way, you can see a virtual table in Power BI table list where you can import multiple objects using the same connection rather than creating a new connection for each custom SQL query.

Be aware, that if you type an invalid SQL query, Power BI may try to import a table instead of importing data using a query. In SQL query, make sure you do not use $ as the table name, e.g. SELECT * FROM $. Use _root_ instead, e.g. SELECT * FROM _root_.

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:

Open ODBC data source configuration and click Copy settings:

ZappySys JSON Driver - Configuration [Version: 2.0.1.10418]

ZappySys JSON Driver - JSON

JSON Connector can be used to extract and output JSON data coming from REST API web service calls (Web URL) or direct JSON String (variables or DB columns) or local JSON files data. JSON Connector also supports JSONPath to filter data from nested array/sub-documents. This Connector is optimized to work with very large JSON string.

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

JsonDSN

DRIVER={ZappySys JSON Driver};DataPath='http://services.odata.org/V3/Northwind/Northwind.svc/Products?$format=json';Filter='$.value[*]';RequestHeaders='Accept: application/json;odata=verbose'
You are good to go! The script will execute the same way as using a DSN.

The DSN defined in the Data source name (DSN) field will be ignored.

Have in mind that a full connection string has length limitations.

Proceed to the next step to find out the details.

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:

Open your ODBC data source.
Click Copy settings button to copy a full connection string (see the previous section on how to accomplish that).
Then create a new file, let's say, in C:\temp\odbc-connection-string.txt.
Continue by pasting the copied connection string into a newly created file and save it.
Finally, the last step! Just construct a shorter ODBC connection string using this format:
```
DRIVER={ZappySys JSON Driver};SettingsFile=C:\temp\odbc-connection-string.txt
```
Our troubles are over! Now you should be able to use this connection string in Power BI with no problems.

This feature requires ODBC PowerPack v1.9.0 or later.

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:

Edit query in Power BI to get REST API data

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

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:

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

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

						
                            = Odbc.Query("dsn=JsonDSN",
                                         "SELECT * FROM _root_ 
                                          WITH (SRC='http://my-api-provider.com/api/" & MyParameter & "/items')")

Use parameter in Power BI to get REST API data

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 JSON 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 JSON 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 JSON via ZappySys Data Gateway.

First, create a data source in ZappySys Data Gateway and create a Linked Server based on it.
Once SQL Server Linked Server is configured we are ready to issue a SQL query in Power BI.
Click Get Data in Power BI, select SQL Server Database
Enter your server name and any database name
Select Mode as DirectQuery
Click on Advanced and enter query like below (we are assuming you have created JSON Data Source in Data Gateway and defined linked server - change the name below).
```
SELECT * FROM OPENQUERY([LS_TO_JSON_IN_GATEWAY], 'SELECT * FROM Tickets')
```
SELECT * FROM OPENQUERY([LS_TO_JSON_IN_GATEWAY], 'SELECT * FROM Tickets')

DirectQuery option for Power BI (Read JSON Data Example using SQL Server Linked Server and ZappySys Data Gateway)
Click OK and Load data... That's it. Now your JSON 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:

First of all, go to Power BI Desktop, open a Power BI report, and click Publish button:
Then select the Workspace you want to publish report to and hit Select button:
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):

Go to Power BI My workspace, hover your mouse cursor on your semantic model and click Settings:
If you see this view, it means you have to install On-premises data gateway (standard mode):
Install On-premises data gateway (standard mode) and sign-in:

Use the same email address you use when logging in into Power BI account.
Register a new gateway (or migrate an existing one):
If you are creating a new gateway, name your gateway, enter a Recovery key, and click Configure button:
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=JsonDSN"}
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=JsonDSN

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.
Proceed by choosing the newly created connection:

ODBC{"connectionstring":"dsn=JsonDSN"}
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):

Go to Power BI My workspace, hover your mouse cursor on your semantic model and click Settings:
If you see this view, it means you have to install On-premises data gateway (personal mode):
Install On-premises data gateway (personal mode) and sign-in:

Use the same email address you use when logging in into Power BI account.
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=JsonDSN
Finally, you are ready to refresh your semantic model:

Configuring pagination in the JSON Driver

ZappySys JSON Driver equips users with powerful tools for seamless data extraction and management from REST APIs, leveraging advanced pagination methods for enhanced efficiency. These options are designed to handle various types of pagination structures commonly used in APIs. Below are the detailed descriptions of these options:

Page-based Pagination: This method works by retrieving data in fixed-size pages from the Rest API. It allows you to specify the page size and navigate through the results by requesting different page numbers, ensuring that you can access all the data in a structured manner.
Offset-based Pagination: With this approach, you can extract data by specifying the starting point or offset from which to begin retrieving data. It allows you to define the number of records to skip and fetch subsequent data accordingly, providing precise control over the data extraction process.
Cursor-based Pagination: This technique involves using a cursor or a marker that points to a specific position in the dataset. It enables you to retrieve data starting from the position indicated by the cursor and proceed to subsequent segments, ensuring that you capture all the relevant information without missing any records.
Token-based Pagination: In this method, a token serves as a unique identifier for a specific data segment. It allows you to access the next set of data by using the token provided in the response from the previous request. This ensures that you can systematically retrieve all the data segments without duplication or omission.

Utilizing these comprehensive pagination features in the ZappySys JSON Driver facilitates efficient data management and extraction from REST APIs, optimizing the integration and analysis of extensive datasets.

For more detailed steps, please refer to this link: How to do REST API Pagination in SSIS / ODBC Drivers

Authentication

ZappySys offers various authentication methods to securely access data from various sources. These authentication methods include OAuth, Basic Authentication, Token-based Authentication, and more, allowing users to connect to a wide range of data sources securely.

ZappySys Authentication is a robust system that facilitates secure access to data from a diverse range of sources. It includes a variety of authentication methods tailored to meet the specific requirements of different data platforms and services. These authentication methods may involve:

OAuth: ZappySys supports OAuth for authentication, which allows users to grant limited access to their data without revealing their credentials. It's commonly used for applications that require access to user account information.
Basic Authentication: This method involves sending a username and password with every request. ZappySys allows users to securely access data using this traditional authentication approach.
Token-based Authentication: ZappySys enables users to utilize tokens for authentication. This method involves exchanging a unique token with each request to authenticate the user's identity without revealing sensitive information.

By implementing these authentication methods, ZappySys ensures the secure and reliable retrieval of data from various sources, providing users with the necessary tools to access and integrate data securely and efficiently. For more comprehensive details on the authentication process, please refer to the official ZappySys documentation or reach out to their support team for further assistance.

For more details, please refer to this link: ZappySys Connections