QuickBooks Source dbt Package (Docs)
- 📣 What does this dbt package do?
- 🎯 How do I use the dbt package?
- 🔍 Does this package have dependencies?
- 🙌 How is this package maintained and can I contribute?
- 🏪 Are there any resources available?
- Materializes QuickBooks staging tables which leverage data in the format described by this ERD. These staging tables clean, test, and prepare your QuickBooks data from
from Fivetran's connector for analysis by doing the following:
- Name columns for consistency across all packages and for easier analysis.
- Adds descriptions to tables and columns that are synced using Fivetran
- Models staging tables, which will be used in our transform package.
- Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
- Generates a comprehensive data dictionary of your source and modeled QuickBooks data through the dbt docs site.
- These tables are designed to work simultaneously with our QuickBooks transformation package
To use this dbt package, you must have the following:
- At least one Fivetran QuickBooks connector syncing data into your destination.
- A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.
If you are not using the QuickBooks transformation package, include the following quickbooks_source package version in your packages.yml file.
TIP: Check dbt Hub for the latest installation instructions or read the dbt docs for more information on installing packages.
packages:
- package: fivetran/quickbooks_source
version: [">=0.9.0", "<0.10.0"] # we recommend using ranges to capture non-breaking changes automaticallyBy default, this package runs using your destination and the quickbooks schema of your target database. If this is not where your QuickBooks data is (for example, if your QuickBooks schema is named quickbooks_fivetran), add the following configuration to your root dbt_project.yml file:
vars:
quickbooks_database: your_destination_name
quickbooks_schema: your_schema_name Your QuickBooks connector might not sync every table that this package expects. This package takes into consideration that not every QuickBooks account utilizes the same transactional tables.
By default, most variables' values are assumed to be true (with exception of using_purchase_order and using_credit_card_payment_txn). In other to enable or disable the relevant functionality in the package, you will need to add the relevant variables:
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 estimates in QuickBooks
using_invoice_bundle: false # disable if you don't have estimates in QuickBooks
using_journal_entry: false # disable if you don't have estimates in QuickBooks
using_payment: false # disable if you don't have estimates in QuickBooks
using_refund_receipt: false # disable if you don't have estimates in QuickBooks
using_transfer: false # disable if you don't have estimates in QuickBooks
using_vendor_credit: false # disable if you don't have estimates in QuickBooks
using_sales_receipt: false # disable if you don't have estimates in QuickBooks
using_purchase_order: true # enable if you want to include purchase orders in your staging models
using_credit_card_payment_txn: true # enable if you want to include credit card payment transactions in your staging modelsExpand for configurations
If you have multiple QuickBooks connectors in Fivetran and would like to use this package on all of them simultaneously, we have provided functionality to do so. The package will union all of the data together and pass the unioned table into the transformations. You will be able to see which source it came from in the source_relation column of each model. To use this functionality, you will need to set either (note that you cannot use both) the quickbooks_union_schemas or quickbooks_union_databases variables:
# dbt_project.yml
...
config-version: 2
vars:
quickbooks_union_schemas: ['quickbooks_us','quickbooks_ca'] # use this if the data is in different schemas/datasets of the same database/project
quickbooks_union_databases: ['quickbooks_us','quickbooks_ca'] # use this if the data is in different databases/projects but uses the same schema nameBy default this package will build the QuickBooks staging models within a schema titled (<target_schema> + _quickbooks_staging) in your target database. If this is not where you would like you QuickBooks staging data to be written to, add the following configuration to your dbt_project.yml file:
# dbt_project.yml
...
models:
quickbooks_source:
+schema: my_new_schema_nameIf an individual source table has a different name than the package expects, add the table name as it appears in your destination to the respective variable:
IMPORTANT: See this project's
dbt_project.ymlvariable declarations to see the expected names.
vars:
quickbooks_<default_source_table_name>_identifier: your_table_name Expand for details
Fivetran offers the ability for you to orchestrate your dbt project through Fivetran Transformations for dbt Core™. Learn how to set up your project for orchestration through Fivetran in our Transformations for dbt Core setup guides.
This dbt package is dependent on the following dbt packages. Please be aware that these dependencies are installed by default within this package. For more information on the following packages, refer to the dbt hub site.
IMPORTANT: If you have any of these dependent packages in your own
packages.ymlfile, we highly recommend that you remove them from your rootpackages.ymlto avoid package version conflicts.
packages:
- package: fivetran/fivetran_utils
version: [">=0.4.0", "<0.5.0"]
- package: dbt-labs/dbt_utils
version: [">=1.0.0", "<2.0.0"]The Fivetran team maintaining this package only maintains the latest version of the package. We highly recommend that 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.
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. Check out this dbt Discourse article to learn how to contribute to a dbt package!
- If you have questions or want to reach out for help, please refer to the GitHub Issue section to find the right avenue of support for you.
- If you would like to provide feedback to the dbt package team at Fivetran or would like to request a new dbt package, fill out our Feedback Form.
- Have questions or want to be part of the community discourse? Create a post in the Fivetran community and our team along with the community can join in on the discussion!
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