Streaming Invoice Data to Google BigQuery

Google BigQuery is a fully managed, serverless data warehouse that scales from a startup's monthly invoices to an enterprise's billions of transaction rows — at the same price and without any infrastructure to manage. For finance teams already in the Google Cloud ecosystem, it's the natural destination for invoice and AR analytics data.

What gets synced to BigQuery

TallyArc streams the following tables into your configured BigQuery dataset:

• invoices — full invoice records with status history
• line_items — granular line item data for product/service revenue analysis
• clients — client master data
• payments — payment events with gateway, method, and amount

Rows are appended in near real-time as events occur — invoice created, invoice paid, payment failed — using BigQuery's streaming insert API.

Service account setup

TallyArc connects to BigQuery via a service account with the minimum required permissions:

1. In GCP, create a service account and grant it the BigQuery Data Editor role on your target dataset
2. Create and download a JSON key for the service account
3. In TallyArc, go to Data → BigQuery → Connect
4. Enter your GCP project ID, dataset name, and paste the full service account JSON
5. Save and run a test sync

Looker Studio dashboards

BigQuery connects directly to Looker Studio (formerly Google Data Studio) — Google's free BI tool. Once your invoice data is in BigQuery:

• Create a Looker Studio data source pointing to your BigQuery dataset
• Build an AR dashboard with: outstanding balance by age, payment trend over time, top clients by revenue, and DSO trend
• Schedule email delivery of the dashboard to your leadership team weekly

Combining invoice data with other Google sources

BigQuery's real power is joining disparate datasets. Common combinations with invoice data:

• Google Analytics + invoices — which acquisition channels produce clients with the best payment behaviour?
• Google Ads spend + invoice revenue — full ROAS accounting including payment speed
• Google Sheets exports — manually maintained client notes or contract terms that enrich invoice analysis

All of this runs in standard SQL inside BigQuery — no ETL tools required for basic joins.