Connecting to Google BigQuery
Google BigQuery is a multi-cloud data warehouse that is used to store all data and analyze it.
Google BigQuery is a fully-managed, serverless data warehouse that enables scalable analysis over petabytes of data. It is a Platform as a Service that supports querying using ANSI SQL. It also has built-in machine learning capabilities.
The Service Account requires storage and BigQuery permissions. The bucket should provide storage permissions to the Service account, under the bucket’s permissions.
There are three options to connect to Google BigQuery:
- Create a new project
- Edit an existing project connection
- Export data from the Export tab>Schedule run button
Connecting to Google BigQuery when Creating a New Project
- Click Enrich. The Enrich page is displayed.gg
- Click 'Create project'. The Create a new project window is displayed.
- Type in a new project name. The project name needs to be unique.
- Select a use case from the drop-down.
- Click Create project. The Upload a dataset window appears.
- Select Google BigQuery.
- Choose a connection name.
- Type in the Bucket Name.
- Upload the service account key JSON.
- Click Upload. Your data is uploaded.
- Click Test Connection to make sure the connection is successful. A message is displayed informing you if the connection was successfully created or not. If the test connection failed, then you are unable to create a connection.
Before creating a new connection, a Test Connection must be run. If the test failed, or a parameter was changed, the Create button will be disabled, and you need to create a new connection. - After the test connection has succeeded, click Create in order to create the connection.
Updated 8 months ago