Visualize Live API Data in the Power BI Service

Power BI transforms your company's data into rich visuals for you to collect and organize so you can focus on what matters to you. When paired with CData Connect AI, you get instant access to API data for visualizations, dashboards, and more. This article shows how to build and publish a dataset from API data in Power BI and then create reports on API data in the Power BI service.

CData Connect AI provides a pure SQL interface for your API, allowing you to easily build reports from live API data in Power BI — with no need to replicate the data. As you build visualizations, Power BI generates SQL queries to gather data. Using optimized data processing out of the box, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc) directly to your API, leveraging server-side processing to quickly return API data.

NOTE: You can also import API data into Power BI through Connect AI (instead of using the on-premise gateway). Read how in the related Knowledge Base article.

Configure your API Connectivity for Power BI

Connectivity to your API from Power BI is made possible through CData Connect AI. To work with API data from Power BI, we start by creating and configuring a your API connection.

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "API" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to your API.

   To connect to your API, configure the following properties on the Global Settings page:

   • In Authentication, select the Type and fill in the required properties
   • In Headers, add the required HTTP headers for your API
   • In Pagination, select the Type and fill in the required properties

   After the configuring the global settings, navigate to the Tables to add tables. For each table you wish to add:

   1. Click "+ Add"
   2. Set the Name for the table
   3. Set Request URL to the API endpoint you wish to work with 👁 Setting the Request URL (Harvest is shown)
      
   4. (Optional) In Parameters, add the required URL Parameters for your API endpoint
   5. (Optional) In Headers, add the required HTTP headers for the API endpoint
   6. In Table Data click " Configure"
   7. Review the response from the API and click "Next" 👁 Reviewing the API response (Harvest is shown)
      
   8. Select which element to use as the Repeated Elements and which elements to use as Columns and click "Next" 👁 Configuring the schema based on the API response(Harvest is shown)
      
   9. Preview the tabular model of the API response and click "Confirm" 👁 Previewing the tabular model of the API response (Harvest is shown)
      
4. Click Save & Test
5. Navigate to the Permissions tab in the Add your API Connection page and update the User-based permissions. 👁 Updating permissions
   

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create. 👁 Creating a new PAT
   
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to API data from Power BI.

Connecting to Connect AI from Power BI

To connect to and visualize live API data in the Power BI service, install the on-premise data gateway, add a data source to the gateway from the Power BI service, and publish a dataset from Power BI Desktop to the service.

Install the On-Premises Data Gateway

The Microsoft on-premise data gateway provides secure data transfer between connected data sources and various cloud-based Microsoft tools and platforms. You can read more about the gateway in the Microsoft documentation.

You can download and install the gateway from the Power BI service:

1. Log in to PowerBI.com.
2. Click the Download menu and click Data Gateway. 👁 Download the Data Gateway
   
3. Follow the instructions for installation, making note of the name of the gateway.

Add your API as a Data Source to the Power BI Service

Once you have installed the data gateway, you add Connect AI as a data source to the Power BI service:

1. Log in to PowerBI.com.
2. Click the Settings menu and click "Manage gateways." 👁 Settings -> Manage gateways
   
3. Click "ADD DATA SOURCE" and configure the connection to Connect AI:
   
   
   • Set Data Source Name to something like ConnectCloudAPI.
   • Choose SQL Server as the Data Source Type.
   • Set Server to tds.cdata.com,14333.
   • Set Database to the name of your your API connection (e.g. API1).
   • Set Authentication Method to Basic.
   • Set Username to a Connect AI user (e.g. [email protected])
   • Set Password to the PAT for the user above.

Publish a Dataset from Power BI Desktop

With the gateway installed and Connect AI added as a datasource to the Power BI service, you can publish a dataset from Power BI Desktop to the service.

1. Open Power BI, click Get Data -> More, then select SQL Server database, and click Connect.
👁 Create a new connection in Power BI

2. Set the connection properties and click OK.
   • Set Server to tds.cdata.com,14333.
   • Set Database to the name of your your API connection (e.g. API1).
   • Set Data Connectivity mode to DirectQuery*.
   👁 Connect to CData Connect AI instance
   * DirectQuery enables live query processing and real-time visualizations of API data.
3. In the authentication wizard, select Database, set the User name and Password properties, and click Connect.
👁 Authenticate the connection

4. Select the table(s) to visualize in the Navigator dialog.
5. In the Query Editor, you can customize your dataset by filtering, sorting, and summarizing your API columns. Click Edit to open the query editor. Right-click a raw to filter the rows. Right-click a column header to perform options like the following:
   • Change column data types
   • Remove a column
   • Group by columns

   Power BI detects each column's data type from the your API metadata reported by Connect AI.

   Power BI records your modifications to the query in the Applied Steps section, adjusting the underlying data retrieval query that is executed to the remote API data. When you click Close and Apply, Power BI executes the data Retrieval query.

   Otherwise, click Load to pull the data into Power BI.

6. Define any relationships between the selected entities on the Relationships tab.
7. Click Publish (from the Home menu) and select a Workspace.

Build Reports and Dashboards on API Data in the Power BI Service

Now that you have published a dataset to the Power BI service, you can create new reports and dashboards based on the published data:

1. Log in to PowerBI.com.
2. Click Workspaces and select a workspace.
3. Click Create and select Report.
4. Select the published dataset for the report. 👁 Select a dataset
   
5. Choose fields and visualizations to add to your report. 👁 Visualizing API data in the Power BI service
   

Live Access to API Data from Cloud Applications

Now you have a direct connection to live API data from the Power BI service. You can create more data sources and new visualizations, build reports, and more — all without replicating API data.

To get live data access to hundreds of SaaS, Big Data, and NoSQL sources directly from your cloud applications, sign up for a free trial of CData Connect AI.