How to Create Power BI Visual Reports with Real-Time BigQuery Data



Use CData Power BI Connectors to visualize BigQuery data in Power BI.

CData Power BI Connectors provide self-service integration with Microsoft Power BI. The CData Power BI Connector for Google BigQuery links your Power BI reports to real-time BigQuery data. You can monitor BigQuery data through dashboards and ensure that your analysis reflects BigQuery data in real time by scheduling refreshes or refreshing on demand. This article details how to use the Power BI Connector to create real-time visualizations of BigQuery data in Microsoft Power BI Desktop.

If you are interested in publishing reports on BigQuery data to PowerBI.com, refer to our other Knowledge Base article.

Collaborative Query Processing

The CData Power BI Connectors offer unmatched performance for interacting with live BigQuery data in Power BI due to optimized data processing built into the connector. When you issue complex SQL queries from Power BI to BigQuery, the connector pushes supported SQL operations, like filters and aggregations, directly to BigQuery and utilizes the embedded SQL Engine to process unsupported operations (often SQL functions and JOIN operations) client-side. With built-in dynamic metadata querying, you can visualize and analyze BigQuery data using native Power BI data types.

About BigQuery Data Integration

CData simplifies access and integration of live Google BigQuery data. Our customers leverage CData connectivity to:

  • Simplify access to BigQuery with broad out-of-the-box support for authentication schemes, including OAuth, OAuth JWT, and GCP Instance.
  • Enhance data workflows with Bi-directional data access between BigQuery and other applications.
  • Perform key BigQuery actions like starting, retrieving, and canceling jobs; deleting tables; or insert job loads through SQL stored procedures.

Most CData customers are using Google BigQuery as their data warehouse and so use CData solutions to migrate business data from separate sources into BigQuery for comprehensive analytics. Other customers use our connectivity to analyze and report on their Google BigQuery data, with many customers using both solutions.

For more details on how CData enhances your Google BigQuery experience, check out our blog post: https://www.cdata.com/blog/what-is-bigquery


Getting Started


Connect to BigQuery as a Power BI Data Source

Installing the Power BI Connector creates a DSN (data source name) called CData Power BI BigQuery. This the name of the DSN that Power BI uses to request a connection to the data source. Configure the DSN by filling in the required connection properties.

You can use the Microsoft ODBC Data Source Administrator to create and configure the DSN: From the Start menu, enter "ODBC Data Sources" and select the CData PowerBI REST DSN. Ensure that you run the version of the ODBC Administrator that corresponds to the bitness of your Power BI Desktop installation (32-bit or 64-bit). You can also use run the ConfigureODBC.exe tool located in the installation folder for the connector.

Google uses the OAuth authentication standard. To access Google APIs on behalf of individual users, you can use the embedded credentials or you can register your own OAuth app.

OAuth also enables you to use a service account to connect on behalf of users in a Google Apps domain. To authenticate with a service account, you will need to register an application to obtain the OAuth JWT values.

In addition to the OAuth values, you will need to specify the DatasetId and ProjectId. See the "Getting Started" chapter of the help documentation for a guide to using OAuth.

How to Query BigQuery Tables

Follow the steps below to build a query to pull BigQuery data into the report:

  1. Open Power BI Desktop and click Get Data -> Other -> CData GoogleBigQuery.
  2. Select CData PowerBI BigQuery in the Data Source Name menu and select a data connectivity mode:
    Select Import if you want to import a copy of the data into your project. You can refresh this data on demand.
    Select DirectQuery if you want to work with the remote data.
  3. Select tables in the Navigator dialog.
  4. In the Query Editor, you can customize your dataset by filtering, sorting, and summarizing BigQuery columns. Click Edit to open the query editor. Right-click a row to filter the rows. Right-click a column header to perform actions like the following:

    • Change column data types
    • Remove a column
    • Group by columns

    Power BI detects each column's data type from the BigQuery metadata retrieved by the connector.

    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 BigQuery data. When you click Close and Apply, Power BI executes the data retrieval query.

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

How to Create Data Visualizations in Power BI

After pulling the data into Power BI, you can create data visualizations in the Report view by dragging fields from the Fields pane onto the canvas. Follow the steps below to create a pie chart:

  1. Select the pie chart icon in the Visualizations pane.
  2. Select a dimension in the Fields pane: for example, OrderName.
  3. Select a measure in the Fields pane: for example, Freight.

You can change sort options by clicking the ellipsis (...) button for the chart. Options to select the sort column and change the sort order are displayed.

You can use both highlighting and filtering to focus on data. Filtering removes unfocused data from visualizations; highlighting dims unfocused data. You can highlight fields by clicking them:

You can apply filters at the page level, at the report level, or to a single visualization by dragging fields onto the Filters pane. To filter on the field's value, select one of the values that are displayed in the Filters pane.

Click Refresh to synchronize your report with any changes to the data.

At this point, you will have a Power BI report built on top of live BigQuery data. Learn more about the CData Power BI Connectors for BigQuery and download a free trial from the CData Power BI Connector for Google BigQuery page. Let our Support Team know if you have any questions.

Ready to get started?

Download a free trial of the Google BigQuery Power BI Connector to get started:

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Learn more:

Google BigQuery Icon Google BigQuery Power BI Connector

The fastest and easiest way to connect Power BI to Google BigQuery data. Includes comprehensive high-performance data access, real-time integration, extensive metadata discovery, and robust SQL-92 support.