Push Data to BigQuery

   Note: Data Warehouse Push is currently only available in beta for Postscript brands on the enterprise plan. To begin using Data Warehouse Push, please be sure to first contact your Customer Success Manager.

Data Warehouse Push allows Postscript to automatically send both historical and new data stored in-app, including clicks, order attribution, and more, to your designated data warehouse. 

In this article, we'll walk you through the three steps for configuring your BigQuery destination.

Before Getting Started

By default, BigQuery authentication uses role-based access. You will need the data-syncing service's service account name available to grant access. It should look like datasync-smsmarkt@prql-prod.iam.gserviceaccount.com.

Step 1: Create service account in BigQuery project

1. In the GCP console, navigate to the IAM & Admin menu, click into the Service Accounts tab, and click Create service account at the top of the menu.

2. In the first step, name the user and click Create and Continue.

3. In the second step, grant the user the role BigQuery User.

Understanding the BigQuery User role

The BigQuery User role is a predefined IAM role that allows for the creation of new datasets, with the creator granted BigQuery Data Owner on the new dataset.

If you would like to avoid using the BigQuery User role, the minimum required permissions are:

  • On the Project level:
  • bigquery.datasets.create
  • bigquery.datasets.get
  • bigquery.jobs.create
Note: These minimum permissions assume that the dataset has not been created ahead of time. If you create the dataset ahead of time, see the following note.

Loading data into a Dataset that already exists

By default, a new dataset (with a name you provide) will be created in the BigQuery project. If instead you create the dataset ahead of time, you will need to grant the BigQuery Data Owner role to this Service Account at the dataset level.

In BigQuery, click on the existing dataset. In the dataset tab, click Sharing, then Permissions. Click Add Principals. Enter the Service Account name, and add the Role: BigQuery Data Owner.

Specifically, the minimum permissions required can be granted to the principal and applied to the Dataset:

  • bigquery.tables.create
  • bigquery.tables.delete
  • bigquery.tables.get
  • bigquery.tables.getData
  • bigquery.tables.list
  • bigquery.tables.update
  • bigquery.tables.updateData
  • bigquery.routines.get
  • bigquery.routines.list

On the Project level, you will still need bigquery.jobs.create, but you will not need bigquery.datasets.create or bigquery.datasets.get.

4. In the third step (Grant users access to this service account step), within the Service account users role field, enter the provided Service account (see prerequisite) and click Done.

5. Once successfully created, search for the created service account in the service accounts list, click the Service account name to view the details, and make a note of the email (note: this is a different email than the service's service account).

6. Select the permissions tab, find the provided principal name (Service account from the prerequisite), click the Edit principal button (pencil icon), click Add another role, select the Service Account Token Creator role, and click Save.

Alternative authentication method: Granting direct access to service account

Role based authentication is the preferred authentication mode for BigQuery based on GCP recommendations, however, providing a service account key to directly log-in to the created service account is an alternative authentication method that can be used if preferred.

1. Back in the Service accounts menu, click the Actions dropdown next to the newly created service account and click Manage keys.

2. Click Add key and then Create new key.

3. Select the JSON Key type and click Create and make note of the key that is generated.

Step 2: Create a staging bucket

1. Log into the Google Cloud Console and navigate to Cloud Storage. Click Create to create a new bucket.

2. Choose a name for the bucket. Click Continue. Select a location for the staging bucket. Make a note of both the name and the location (region).

Choosing a location (region)

The location you choose for your staging bucket must match the location of your destination dataset in BigQuery. When creating your bucket, be sure to choose a region in which BigQuery is supported (see BigQuery regions)

  • If the dataset does not exist yet, the dataset will be created for you in the same region where you created your bucket.
  • If the dataset does exist, the dataset region must match the location you choose for your bucket.

3. Click continue and select the following options according to your preferences. Once the options have been filled out, click Create.

4. On the Bucket details page that appears, click the Permissions tab, and then click Add.

5. In the New principles dropdown, add the Service Account created in Step 1, select the Storage Admin role, and click Save.

Step 3: Find Project ID

  1. Log into the Google Cloud Console and select the projects list dropdown.
  2. Make note of the BigQuery Project ID

Step 4: Add your destination

Securely share your Project ID, Bucket Name, Bucket Location, Destination Schema Name and Service Account name with us to complete the connection.

Get Support

Have questions? Please feel free to reach out to our wonderful Support team at support@postscript.io or via live chat. You can also submit a support request here!

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