Most Data Analytics stacks comprise three stages: an ETL (Extract, Transform, Load) tool, a Data Warehouse for data centralization, and a visualization or BI (Business Intelligence) tool. This article demonstrates how to use Microsoft Power BI as a BI tool, along with BigQuery as the Data Warehouse and Kondado as the ETL tool.
3. Creating your first integration: Now that your data destination and data sources are registered, you can create your first integration by following the platform onboarding steps.
5.Connecting BigQuery to Power BI:
- On the Power BI home page, click on “Get Data” in the top bar:
- Select the “Database” option in the side menu:
- Then choose the “Google BigQuery” option from the list and click on “Connect”:
- In the screen that opens, a message will appear that you are not connected to BigQuery. Then click on “Sign in”:
- A Google login screen will open, where you must enter your email, and on the next screen the password, which has access to Google BigQuery:
- After entering the password, click on “Allow” or “Permit” so that Power BI gains access to your BigQuery:
- You will return to the previous screen, which will inform you that you are connected to BigQuery. Then click on “Connect”:
- Now you need to choose from a list which BigQuery tables you want to bring into Power BI (remember to search for the names of the tables you defined when creating your integration in Kondado, according to step 4). Just check the selection box next to the name of the tables and click on “Load” once all are selected:
- In this step, Power BI asks you to choose a connection setting. We recommend using “DirectQuery” so that the data is updated in real-time, as it is updated in BigQuery:
- Done! Now your BigQuery is connected to Power BI and your data will be available for viewing or transforming whenever you need it: