QuickBooks (docs)

This package models QuickBooks data from Fivetran's connector. It uses data in the format described by this ERD.

The main focus of this package is to provide users insights into their QuickBooks data that can be used for financial statement reporting and deeper analysis. The package achieves this by:

• Creating a comprehensive general ledger that can be used to create financial statements with additional flexibility.
• Providing historical general ledger month beginning balances, ending balances, and net change for each account.
• Enhancing Accounts Payable and Accounts Receivables data by providing past and present aging of bills and invoices.
• Pairing all expense and sales transactions in one table with accompanying data to provide enhanced analysis.

Compatibility

Please be aware that the dbt_quickbooks and dbt_quickbooks_source packages were developed with single currency company data. As such, the package models will not reflect accurate totals if your QuickBooks account has Multi-Currency enabled.

Models

This package contains transformation models designed to work simultaneously with our QuickBooks source package. A dependency on the source package is declared in this package's packages.yml file, so it will automatically download when you run dbt deps. The primary outputs of this package are described below. Intermediate models are used to create these output models.

model	description
quickbooks__general_ledger	Table containing a comprehensive list of all transactions with offsetting debit and credit entries to accounts.
quickbooks__general_ledger_by_period	Table containing the beginning balance, ending balance, and net change of the dollar amount for each month since the first transaction. This table can be used to generate a balance sheet and income statement for your business.
quickbooks__profit_and_loss	Table containing all revenue and expense account classes by calendar year and month enriched with account type, class, and parent information.
quickbooks__balance_sheet	Table containing all asset, liability, and equity account classes by calendar year and month enriched with account type, class, and parent information.
quickbooks__ap_ar_enhanced	Table providing the amount, amount paid, due date, and days overdue of all bills and invoices your company has received and paid along with customer, vendor, department, and address information for each invoice or bill.
quickbooks__expenses_sales_enhanced	Table providing enhanced customer, vendor, and account details for each expense and sale transaction.

Installation Instructions

Check dbt Hub for the latest installation instructions, or read the dbt docs for more information on installing packages.

Include in your packages.yml

packages:
  - package: fivetran/quickbooks
    version: [">=0.4.0", "<0.5.0"]

Configuration

By default, this package looks for your QuickBooks data in the quickbooks schema of your target database. If this is not where your QuickBooks data is, add the below configuration to your dbt_project.yml file.

# dbt_project.yml

...
config-version: 2

vars:
    quickbooks_database: your_database_name
    quickbooks_schema: your_schema_name

Changing the Build Schema

By default this package will build the QuickBooks staging models within a schema titled (<target_schema> + _quickbooks_staging) and QuickBooks final models within a schema titled (<target_schema> + _quickbooks) in your target database. If this is not where you would like your modeled QuickBooks data to be written to, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

...
models:
    quickbooks:
      +schema: my_new_schema_name # leave blank for just the target_schema
    quickbooks_source:
      +schema: my_new_schema_name # leave blank for just the target_schema

Disabling models

This package takes into consideration that not every QuickBooks account utilizes the same transactional tables, and allows you to disable the corresponding functionality. By default, most variables' values are assumed to be true (with exception of purchase orders). Add variables for only the tables you want to disable or enable respectively:

# dbt_project.yml

...
vars:
  using_address:        false         #disable if you don't have addresses in QuickBooks
  using_bill:           false         #disable if you don't have bills or bill payments in Quickbooks
  using_credit_memo:    false         #disable if you don't have credit memos in Quickbooks
  using_department:     false         #disable if you don't have departments in Quickbooks
  using_deposit:        false         #disable if you don't have deposits in Quickbooks
  using_estimate:       false         #disable if you don't have estimates in Quickbooks
  using_invoice:        false         #disable if you don't have invoices in Quickbooks
  using_invoice_bundle: false         #disable if you don't have invoice bundles in Quickbooks
  using_journal_entry:  false         #disable if you don't have journal entries in Quickbooks
  using_payment:        false         #disable if you don't have payments in Quickbooks
  using_refund_receipt: false         #disable if you don't have refund receipts in Quickbooks
  using_transfer:       false         #disable if you don't have transfers in Quickbooks
  using_vendor_credit:  false         #disable if you don't have vendor credits in Quickbooks
  using_sales_receipt:  false         #disable if you don't have sales receipts in QuickBooks
  using_purchase_order: true          #enable if you want to include purchase orders in your staging models

Analysis

After running the models within this package, you may want to compare the baseline financial statement totals from the data provided against what you expect. You can make use of the analysis functionality of dbt and run pre-written SQL to test these values. The SQL files within the analysis folder contain SQL queries you may compile to generate balance sheet and income statement values. You can then tie these generated values to your expected ones and confirm the values provided in this package are accurate.

Contributions

Don't see a model or specific metric you would have liked to be included? Notice any bugs when installing and running the package? If so, we highly encourage and welcome contributions to this package! Please create issues or open PRs against main. Check out this post on the best workflow for contributing to a package.

Database Support

This package has been tested on BigQuery, Snowflake, Redshift, and Postgres.

Resources:

• Provide feedback on our existing dbt packages or what you'd like to see next
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• Learn how to orchestrate dbt transformations with Fivetran here.
• Learn more about Fivetran overall in our docs
• Check out Fivetran's blog
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