Quickbooks dbt Package

This dbt package transforms data from Fivetran's Quickbooks connector into analytics-ready tables.

Resources

Number of materialized models¹: 108
Connector documentation
- Quickbooks connector documentation
- Quickbooks ERD
dbt package documentation

What does this dbt package do?

This package enables you to create comprehensive financial statements, analyze accounts payable and receivable aging, and track detailed transaction histories. It creates enriched models with metrics focused on general ledger analysis, financial reporting, and cash flow management.

Output schema

Final output tables are generated in the following target schema:

<your_database>.<connector/schema_name>_quickbooks

Final output tables

By default, this package materializes the following final tables:

Table	Description
quickbooks__general_ledger	Complete transaction-level view showing every debit and credit entry with running account balances, perfect for detailed financial analysis and audit trails. Example Analytics Questions: Which accounts show consistent growth patterns that indicate successful business strategies? What transaction patterns and account behaviors provide the clearest operational insights?
quickbooks__general_ledger_by_period	Monthly account balance summary showing beginning balances, ending balances, and net changes for each account, ideal for generating financial statements and tracking account performance over time. Example Analytics Questions: Which accounts demonstrate the strongest month-over-month improvement and growth momentum? What seasonal patterns and cyclical trends can inform better financial planning and budgeting?
quickbooks__profit_and_loss	Income statement view showing revenue and expense accounts by month and year, with configurable ordering for professional financial reporting. Example Analytics Questions: Which revenue streams and cost optimizations are driving the strongest profit growth? What expense-to-revenue ratios and margin trends provide the clearest profitability insights?
quickbooks__balance_sheet	Balance sheet view displaying assets, liabilities, and equity accounts by month and year, organized for standard financial statement presentation. Example Analytics Questions: Which asset investments are generating the strongest returns and should be expanded? What debt-to-equity ratios and financial leverage trends indicate optimal capital structure?
quickbooks__cash_flow_statement	Cash flow statement showing operating, investing, and financing activities with beginning/ending cash positions and net changes by period. IMPORTANT: You will likely need to configure cash flow types for your specific use case. Example Analytics Questions: Which operational improvements are generating the strongest positive cash flow trends? What seasonal cash flow patterns and financing needs can inform strategic planning?
quickbooks__ap_ar_enhanced	Accounts payable and receivable aging report showing outstanding bills and invoices with payment history, due dates, and overdue analysis for cash flow management. Example Analytics Questions: Which customers have the best payment patterns and deserve credit limit increases or early payment discounts? What payment timing patterns and customer behavior trends can optimize cash flow forecasting?
quickbooks__expenses_sales_enhanced	Unified view of all expense and sales transactions with enriched customer, vendor, department, and product details for comprehensive revenue and cost analysis. Example Analytics Questions: Which customer segments and product lines deliver the highest margins and growth potential? What departmental spending patterns and vendor relationships provide the best cost optimization opportunities?

¹ Each Quickstart transformation job run materializes these models if all components of this data model are enabled. This count includes all staging, intermediate, and final models materialized as view, table, or incremental.

Multicurrency Support

This package now supports multicurrency by bringing in values by specifying *_converted_* values for cash amounts. More details are available in the DECISIONLOG.

Prerequisites

To use this dbt package, you must have the following:

At least one Fivetran Quickbooks connection syncing data into your destination.
A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.

How do I use the dbt package?

You can either add this dbt package in the Fivetran dashboard or import it into your dbt project:

To add the package in the Fivetran dashboard, follow our Quickstart guide.
To add the package to your dbt project, follow the setup instructions in the dbt package's README file to use this package.

How is this package maintained and can I contribute?

Package Maintenance

The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend you stay consistent with the latest version of the package and refer to the CHANGELOG and release notes for more information on changes across versions.

Contributions

A small team of analytics engineers at Fivetran develops these dbt packages. However, the packages are made better by community contributions.

We highly encourage and welcome contributions to this package. Learn how to contribute to a package in dbt's Contributing to an external dbt package article.

Opinionated Modelling Decisions

This dbt package takes an opinionated stance on how to define the ordering and cash flow types in our model based on best financial practices. Customers do have the option to customize these orderings and cash flow types with a seed file. Instructions are available in the Additional Configuration section. If you would like a deeper explanation of the logic used by default or for more insight into certain modeling practices within this dbt package, you may reference the DECISIONLOG.