Throughout the open beta period, both pipelines are available for free for all OWOX BI plans with a paid subscription.
1. On the OWOX BI main page, click Create pipeline:
2. As a source, select Facebook:
3. As a destination, select Google BigQuery:
4. Select or add new access to a Facebook account from which you want to export ad cost data from:
5. Select or add new access to a Google BigQuery account where you want to store the exported data:
6. Select a Google BigQuery project and create a dataset you want to upload your data to (or create an existing one):
Note: To set up the data collection successfully, your Google account must have "BigQuery Data Editor" and "BigQuery User" roles in the project where you want to collect data to. Without this permission, BigQuery won’t let you upload the data.
7. Specify the date that marks the beginning of the period you want to upload cost data for:
You can schedule the start of the import on a date in the future or select a past date to upload historical data from the Facebook account.
Also at this step, specify the VAT rate to exclude from the exported costs. You need this to have your Facebook cost data consistent with the cost data from other services where VAT is being excluded automatically.
8. Click Create pipeline.
Done! The pipeline will be uploading data to a partitioned table in the selected BigQuery dataset. The data will be uploaded daily — for the previous day.
OWOX BI will also update the data already uploaded to BigQuery if the data in the Facebook account would change retrospectively. The update period for historical data is 21 days. This means that 21 days after the import, the data in BigQuery will be totally up-to-date.
The data this pipeline uploads from Facebook is listed in this article.
Under this pipeline, OWOX BI processes UTM tags in the ad links that were modified via the URL tracking or shortening services (for example, ad.doubleclick.net, weborama, bit.ly).