You can import data from Google BigQuery to create source datasets in Anaplan Data Orchestrator (ADO). To import data, you need a connection to Google BigQuery and either a pipeline or a connection extract.

You must first create a connection to Google BigQuery with the BigQuery connector in ADO. Then use that connection to either create a pipeline or use a connection extract for data import.

Connectivity prerequisites

Before you can create a connection to Google BigQuery, you need to meet these prerequisites.

ItemNotes
Google Cloud Platform account

You can access the Google Cloud Platform with a Google account.

The Anaplan connection authenticates to BigQuery using Google Cloud service account and a JSON key file (a text file with a .json extension). 

The required BigQuery permissions must be granted to that service account. 

Google BigQuery permissions 

You need these BigQuery project-level roles granted to the service account:

  • roles/bigquery.jobUser: Lets the connection run queries.
  • roles/bigquery.user: Lets the connection use BigQuery in the project.

To read data, the service account also needs roles/bigquery.dataViewer granted on the table or dataset you want to read.


For more information, see the Google BigQuery documentation about the roles and permissions needed.

Create a connection to Google BigQuery

You will need your Google BigQuery credentials to connect the BigQuery data with Data Orchestrator. View the BigQuery documentation for more information about your credentials.

To create a connection:

  1. Select Data Orchestrator from the top-left navigation menu.
  2. Choose a dataspace from the list.
  3. Select Connections from the left-side panel.
  4. Select Create connection.
  5. Select the BigQuery connector and then select Next.
    If you can't find the connector, enter a search term in the Find... field.
  6. Enter these details on the Connection details screen, and then select Next:
    • Name: Create a name for your connection. The name can contain alphanumeric characters and underscores.
    • Description: Enter a description about your connection.
  7. Enter your BigQuery credentials on the Connection credentials screen, and then select Next.
    • Project ID: The identifier for the BigQuery project that contains the dataset (for example, myproject-1234).
    • Credentials Json: The BigQuery JSON code for authentication.
    • Dataset ID: The BigQuery dataset ID.
      (If you use the Google BigQuery connection to extract data, only the views defined under the Dataset ID for the connection definition are visible under Path name.)
  8. After the connection test is complete, select Done.

Import data

You can import data from BigQuery with a pipeline or a connection extract. Use the connection you created to configure the pipeline or connection extract.

Data type mapping for Google BigQuery

Datasets imported from Google BigQuery are mapped to ADO data types. For more information, see Data mapping for Google BigQuery.