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Join marketing, finance, CRM, and product data inside the same warehouse.
Available metrics
Available dimensions
Select your Google Cloud project and BigQuery dataset. Catchr automatically prepares the destination and maps your data into analytics-ready tables.
Catchr continuously imports new and updated data into BigQuery.
Your warehouse stays fresh automatically, ready for SQL, dbt, BI tools, and AI workloads.
Open the dedicated route for each platform. Its field catalog, reporting grain, historical constraints, and warehouse use cases should be specific to that source.
Answers about available Meta Ads data, reporting cadence, history, table settings, attribution changes, and downstream joins.
Add Facebook Ads as a source in Catchr, choose BigQuery as the destination, select the fields to export, and authorize the target Google Cloud project and dataset.
Export account, campaign, ad group, ad, creative, audience, spend, impression, click, conversion, and revenue fields available from this advertising source.
Schedule recurring refreshes in Catchr so your BigQuery tables stay updated automatically. Available frequencies depend on your plan, source limits, and reporting needs.
Yes. Keep sources in separate tables, then use SQL views or models to join them on shared dimensions such as date, campaign, account, customer, product, or region.
Build campaign reports, budget pacing, attribution models, cross-channel dashboards, and long-term performance history without relying on manual exports.
If your selected schema contains an eligible date field, you can configure that field as the optional date partition for the destination table. Catchr does not configure table clustering or design your downstream analytical models.
Yes. Configure the historical period supported by the source for the initial import, then keep the table updated with recurring exports. The available range is determined by the source API and the settings of your job, not an unlimited-history promise.
It depends on what you need to report on. The BigQuery Data Transfer Service ships a Facebook Ads connector that loads twelve fixed reports, among them AdInsights, Ads, AdSets, Campaigns, and AdCreatives. If those tables cover your questions and a daily refresh is enough, it does the job. Catchr answers a different need: you choose the fields rather than take a fixed schema, you set the refresh rhythm, and you add your other platforms to the same warehouse through one connection instead of one transfer configuration per source.
Google documents them clearly. Transfers run once a day at most, and the interval cannot go below 24 hours. Custom reports are not supported, only the fixed table set. The refresh window is capped at 30 days and cannot be configured, and it only applies to the AdInsights and AdInsightsActions tables. A transfer that runs longer than six hours fails. Setup needs a Facebook developer app of type Business, with its app ID and app secret, and the BigQuery Admin role on the project. The long-lived access token expires every 60 days and has to be regenerated by hand. Support for the AdInsightsMMM report has been temporarily disabled since July 6, 2026.
No. Google bills the Facebook Ads connector as a paid connector in the BigQuery Data Transfer Service, charged on the compute the transfer consumes, measured in slot-hours, on top of your storage and query costs. The connectors Google provides for its own sources, such as Google Ads, Google Analytics 4, and Campaign Manager, are the ones that carry no transfer charge. Facebook Ads is not one of them.
Our teams is always here to respond to any question you could have about our data connector.
Connect your accounts, choose the fields then send the configured export to your BigQuery project.