Netsuite

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

This package enriches your Fivetran data by doing the following:

• Adds descriptions to tables and columns that are synced using Fivetran
• Adds freshness tests to source data
• Adds column-level testing where applicable. For example, all primary keys are tested for uniqueness and non-null values.
• Models staging tables, which will be used in our transform package

Requirementslink

A Fivetran NetSuite Analytics connector, with the following tables synced:

• 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

Modelslink

This package contains staging models, designed to work simultaneously with our netsuite transformation package. The staging models:

• Remove any rows that are soft-deleted
• Name columns consistently across all packages:
  • Boolean fields are prefixed with is_ or has_
  • Timestamps are appended with _at
  • Columns are renamed to fit consistency of other fields. For example, the accounts accountnumber field is renamed to account_number.

Installation Instructionslink

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/netsuite_source
    version: [">=0.4.0", "<0.5.0"]

Configurationlink

By default, this package will run using your target database and the netsuite schema. If this is not where your netsuite data is (perhaps your netsuite schema is netsuite_fivetran), add the following configuration to your dbt_project.yml file:

...
vars:
  netsuite_source:
    netsuite_database: your_database_name
    netsuite_schema: your_schema_name

Passthrough Columnslink

This package includes all source columns defined in the macros folder. To add additional columns to this package, do so using our pass-through column variables. This is extremely useful if you’d like to include custom fields to the package.

...
vars:
  netsuite_source:
    accounts_pass_through_columns: ['new_custom_field', 'we_can_account_for_that']
    classes_pass_through_columns: ['class_is_in_session', 'pass_through_additional_fields_here']
    departments_pass_through_columns: ['department_custom_fields']
    transactions_pass_through_columns: ['transactions_can_be_custom','pass_this_transaction_field_on']
    transaction_lines_pass_through_columns: ['transaction_lines_field']
    customers_pass_through_columns: ['customers_field']
    locations_pass_through_columns: ['this_new_location','lets_also_add_this_location_field']
    subsidiaries_pass_through_columns: ['subsidiaries_field']
    consolidated_exchange_rates_pass_through_columns: ['this_exchange_rate','that_exchange_rate']

Changing the Build Schemalink

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

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

Contributionslink

Additional contributions to this package are very welcome! Please create issues or open PRs against main. Check out this post on the best workflow for contributing to a package.

Database supportlink

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

Resources:link

• Provide feedback on our existing dbt packages or what you’d like to see next
• Have questions, feedback, or need help? Book a time during our office hours here or email us at solutions@fivetran.com
• Find all of Fivetran’s pre-built dbt packages in our dbt hub
• Learn how to orchestrate your models with Fivetran Transformations for dbt Core™
• Learn more about Fivetran overall in our docs
• Check out Fivetran’s blog
• Learn more about dbt in the dbt docs
• Check out Discourse for commonly asked questions and answers
• Join the chat on Slack for live discussions and support
• Find dbt events near you
• Check out the dbt blog for the latest news on dbt’s development and best practices