Netsuite dbt Package
This dbt package transforms data from Fivetran's Netsuite connector into analytics-ready tables.
Resources
- Number of materialized models¹: 92
- Connector documentation
- dbt package documentation
What does this dbt package do?
This package enables you to recreate both the balance sheet and income statement, and recreate commonly used data by using the transaction lines as the base table and joining other data. It creates enriched models with metrics focused on financial statement reporting and deeper transactional analysis.
Output schema
Final output tables are generated in the following target schema:
<your_database>.<connector/schema_name>_netsuite
Final output tables
By default, this package materializes the following final tables:
| Table | Description |
|---|---|
| netsuite2__balance_sheet | Creates all transaction lines necessary to generate a balance sheet with proper currency conversion for the parent subsidiary. Non-balance sheet transactions are categorized as Retained Earnings or Net Income, with manual calculation of Cumulative Translation Adjustment. Example Analytics Questions:
|
| netsuite2__income_statement | Provides all transaction lines needed for income statement generation with currency conversion and department, class, and location details for enhanced reporting capabilities. Example Analytics Questions:
|
| netsuite2__transaction_details | Comprehensive transaction-level view combining transaction lines with detailed context including accounting period, account, subsidiary, customer, vendor, location, item, and department information. Example Analytics Questions:
|
| netsuite2__entity_subsidiary_relationships | Unified view of customer and vendor relationships across subsidiaries, showing which entities operate in which subsidiaries with primary subsidiary designations and currency details. Example Analytics Questions:
|
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.
Visualizations
Many of the above reports are now configurable for visualization via Streamlit. Check out some sample reports here.
Prerequisites
To use this dbt package, you must have the following:
- At least one Fivetran Netsuite 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.
To use this dbt package, you must have at least one Fivetran Netsuite (netsuite.com) or Netsuite2 (netsuite2) connection syncing the respective tables to your destination:
Netsuite.com
- accounts
- accounting_periods
- accounting_books
- consolidated_exchange_rates
- currencies
- customers
- classes
- departments
- expense_accounts
- income_accounts
- items
- locations
- partners
- transaction_lines
- transactions
- subsidiaries
- vendors
- vendor_types
Netsuite2
- account
- accountingperiod
- currency
- customer
- transactionaccountingline
- transactionline
- transaction
- subsidiary
- vendor
- Not required but recommended:
- accounttype
- accountingbook
- accountingbooksubsidiary
- accountingperiodfiscalcalendar
- accountingbook
- classification
- consolidatedexchangerate
- department
- entity
- entityaddress
- fiscalcalendar (required for non–January 1 fiscal year start)
- item
- job
- location
- locationmainaddress
- nexus
- vendorcategory
- vendorsubsidiaryrelationship
All required sources and staging models are now bundled into this transformation package. Do not include
fivetran/netsuite_sourcein yourpackages.ymlsince this package has been deprecated.
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.
