How often does Kondado update Granatum data in BigQuery?

Kondado replicates Granatum data on a configurable schedule that you control, with options ranging from every 5 minutes to daily updates. You can set different frequencies for different pipelines based on your reporting needs, ensuring your BigQuery datasets reflect the most recent financial activity without overwhelming your source system.

What Granatum data can I analyze in BigQuery?

You can replicate six distinct pipelines including Bank Accounts with current balances, detailed Transactions with values and due dates, and Clients with contact information. The Categories and Cost and Profit Centers pipelines enable hierarchical analysis of your financial structure, while Payment Methods data helps you understand transaction preferences across your customer base.

Can I combine Granatum data with other sources in BigQuery?

Yes, once your Granatum data lands in BigQuery, you can join it with information from your CRM, marketing platforms, or PostgreSQL databases. This enables unified reporting that connects your financial metrics with sales pipelines or advertising spend for complete business visibility.

Does Kondado create separate datasets for each Granatum pipeline?

Kondado loads each pipeline into your specified BigQuery dataset as individual tables that you can query using standard SQL. The schema preserves Granatum field names and data types, making it straightforward to build custom views and reports that reference Bank Accounts, Transactions, and Client records together.

How do I start sending Granatum data to BigQuery without coding?

Begin by adding Granatum as a data source using your API credentials, then authenticate your BigQuery project connection. Select which pipelines to replicate, configure your update schedule, and Kondado manages the rest, delivering structured financial data ready for analysis in Looker Studio or SQL queries.

What happens to historical Granatum data when I first connect?

Kondado performs an initial full replication of your selected Granatum pipelines, loading historical records into BigQuery based on your configuration. After the initial load, the pipeline continues with incremental updates on your chosen schedule, keeping your dataset current without reprocessing existing records.

Can I send Granatum data to BigQuery and Power BI simultaneously?

Yes, you can configure multiple destinations for your Granatum data source, sending the same financial information to BigQuery and Power BI concurrently. This allows different teams to access Granatum data in their preferred analytics environment while maintaining consistent, synchronized datasets across platforms.

How is Granatum data formatted when it arrives in BigQuery?

Granatum data arrives as structured tables with preserved field names and appropriate data types for financial analysis. Date fields maintain proper timestamp formats for time-series analysis, while monetary values retain decimal precision, enabling accurate calculations for balance tracking and transaction reporting directly within your BigQuery environment.

Send data from Granatum to BigQuery

Get started for free

No credit card required | 14 days | 10 million records | 30 pipelines

or sign up with your email

By signing up, you agree to Kondado’s Terms of service and Privacy policy

Send Granatum Data to BigQuery Automatically

To send Granatum data to BigQuery, connect your Granatum account as a data source on Kondado, select BigQuery as your destination, and choose which pipelines to replicate. Kondado handles the data extraction and loading automatically on your chosen schedule, eliminating manual exports and CSV uploads. Your financial data from Granatum becomes available in BigQuery for analysis alongside other business data sources.

Kondado provides a direct integration between Granatum and BigQuery, replicating Bank Accounts, Transactions, Categories, Cost and Profit Centers, Payment Methods, and Clients data on a configurable schedule ranging from every 5 minutes to daily, with no coding required.

Once configured, your Granatum financial records flow continuously into your BigQuery dataset, ready for SQL queries and business intelligence. This automated pipeline ensures your cash flow analysis, expense tracking, and client management data stay current without manual intervention.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Replicate your Bank Accounts and Transactions pipelines to build comprehensive cash flow dashboards in BigQuery, tracking balances and due dates across multiple accounts on a configurable schedule. Combine this with the Clients pipeline to analyze payment patterns by customer segment or geographic region, enabling targeted financial strategies and customer retention efforts. You can also leverage the Cost and Profit Centers pipeline to attribute transactions accurately across business units, creating granular profitability reports that drive smarter decision-making. Once in BigQuery, join Granatum financial data with marketing or sales metrics from other sources for unified business intelligence.

Try out all the features for free for 14 days

Granatum data available for BigQuery

available pipelines

extractable fields

Available integrations

Integration	Description
Bank Accounts	Table contains information about bank accounts, including fields such as id, description, and balance.
Transactions	Table records financial transactions with fields such as id, description, value, and due date.
Categories	Table lists categories with fields such as id, description, and color, allowing for the organization of transactions.
Cost and Profit Centers	Table presents cost and profit centers with fields such as id, description, and parent_id for hierarchy.
Payment Methods	Table details payment methods with fields such as id and description, facilitating transaction management.
Clients	Table contains client data, including fields such as name, email, phone, and address.