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Netsuite Source dbt Package (Docs)

What does this dbt package do?

  • Materializes Netsuite staging tables which leverage data in the format described by this ERD. These staging tables clean, test, and prepare your Netsuite data from Fivetran's connector for analysis by doing the following:
    • Name columns for consistency across all packages and for easier analysis
    • 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.
  • Generates a comprehensive data dictionary of your netsuite data through the dbt docs site.
  • These tables are designed to work simultaneously with our Netsuite transformation package.

How do I use the dbt package?

Step 1: Prerequisites

To use this dbt package, you must have At least either one Fivetran Netsuite (netsuite.com) or Netsuite2 (netsuite2) connector 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
  • accounttype
  • accountingbooksubsidiary
  • accountingperiodfiscalcalendar
  • accountingperiod
  • accountingbook
  • consolidatedexchangerate
  • currency
  • customer
  • classification
  • department
  • employee
  • entity
  • entityaddress
  • item
  • job
  • location
  • locationmainaddress
  • transactionaccountingline
  • transactionline
  • transaction
  • subsidiary
  • vendor
  • vendorcategory

Database Compatibility

This package is compatible with either a BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.

Databricks dispatch configuration

If you are using a Databricks destination with this package, you must add the following (or a variation of the following) dispatch configuration within your dbt_project.yml. This is required in order for the package to accurately search for macros within the dbt-labs/spark_utils then the dbt-labs/dbt_utils packages respectively.

dispatch:
  - macro_namespace: dbt_utils
    search_order: ['spark_utils', 'dbt_utils']

Step 2: Install the package (skip if also using the Netsuite transformation package)

If you are not using the Netsuite transformation package, include the following package version in your packages.yml file. If you are installing the transform package, the source package is automatically installed as a dependency.

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

packages:
  - package: fivetran/netsuite_source
    version: [">=0.11.0", "<0.12.0"]

Step 3: Define Netsuite.com or Netsuite2 Source

As of April 2022 Fivetran made available a new Netsuite connector which leverages the Netsuite2 endpoint opposed to the original Netsuite.com endpoint. This package is designed to run for either or, not both. By default the netsuite_data_model variable for this package is set to the original netsuite value which runs the netsuite.com version of the package. If you would like to run the package on Netsuite2 data, you may adjust the netsuite_data_model variable to run the netsuite2 version of the package.

vars:
    netsuite_data_model: netsuite2 #netsuite by default

Step 4: Define database and schema variables

By default, this package runs using your destination and the netsuite schema. If this is not where your Netsuite data is (for example, if your netsuite schema is named netsuite_fivetran), add the following configuration to your root dbt_project.yml file:

vars:
    netsuite_database: your_destination_name
    netsuite_schema: your_schema_name

Step 5: Disable models for non-existent sources (Netsuite2 only)

It's possible that your Netsuite connector does not sync every table that this package expects. If your syncs exclude certain tables, it is because you either don't use that feature in Netsuite or actively excluded some tables from your syncs. To disable the corresponding functionality in the package, you must add the relevant variables. By default, all variables are assumed to be true. Add variables for only the tables you would like to disable:

vars:
    netsuite2__multibook_accounting_enabled: false # True by default. Disable `accountingbooksubsidiary` and `accountingbook` if you are not using the Multi-Book Accounting feature
    netsuite2__using_exchange_rate: false #True by default. Disable `exchange_rate` if you don't utilize exchange rates. If you set this variable to false and are using the `netsuite` transformation package, ensure it is scoped globally so that the `netsuite` package can access it as well.  
    netsuite2__using_vendor_categories: false # True by default. Disable `vendorcategory` if you don't categorize your vendors
    netsuite2__using_jobs: false # True by default. Disable `job` if you don't use jobs
    netsuite2__using_employees: false # True by default. Disable `employee` if you don't use employees.

Note: The Netsuite dbt package currently only supports disabling transforms of Multi-Book Accounting related tables (accountingbooksubsidiary and accountingbook), the vendorcategory source table, and the job source table. Please create an issue to request additional tables and/or features to exclude.

To determine if a table or field is activated by a feature, access the Records Catalog.

(Optional) Step 6: Additional configurations

Expand for configurations

Passing Through Additional Fields

This package includes all source columns defined in the macros folder. You can add more columns using our pass-through column variables. These variables allow for the pass-through fields to be aliased (alias) and casted (transform_sql) if desired, but not required. Datatype casting is configured via a sql snippet within the transform_sql key. You may add the desired sql while omitting the as field_name at the end and your custom pass-though fields will be casted accordingly. Use the below format for declaring the respective pass-through variables:

vars:
    accounts_pass_through_columns: 
        - name: "new_custom_field"
          alias: "custom_field"
    classes_pass_through_columns: 
        - name: "this_field"
    departments_pass_through_columns: 
        - name: "unique_string_field"
          alias: "field_id"
          transform_sql: "cast(field_id as string)"
    transactions_pass_through_columns: 
        - name: "that_field"
    transaction_lines_pass_through_columns: 
        - name: "other_id"
          alias: "another_id"
          transform_sql: "cast(another_id as int64)"
    customers_pass_through_columns: 
        - name: "customer_custom_field"
          alias: "customer_field"
    entities_pass_through_columns:
        - name: "entity_custom_field"
          alias: "entity_field"
    locations_pass_through_columns: 
        - name: "location_custom_field"
    subsidiaries_pass_through_columns: 
        - name: "sub_field"
          alias: "subsidiary_field"
    consolidated_exchange_rates_pass_through_columns: 
        - name: "consolidate_this_field"
    vendors_pass_through_columns: 
        - name: "vendors_custom_field"
          alias: "vendors_field"
    items_pass_through_columns: 
        - name: "items_custom_field"
          alias: "items_field"

Change the build schema

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

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

Change the source table references

If 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.yml variable declarations to see the expected names.

vars:
    # For all Netsuite source tables
    netsuite_<default_source_table_name>_identifier: your_table_name 

    # For all Netsuite2 source tables
    netsuite2_<default_source_table_name>_identifier: your_table_name

Override the data models variable

This package is designed to run either the Netsuite.com or Netsuite2 data models. However, for documentation purposes, an additional variable netsuite_data_model_override was created to allow for both data model types to be run at the same time by setting the variable value to netsuite. This is only to ensure the dbt docs (which is hosted on this repository) is generated for both model types. While this variable is provided, we recommend you do not adjust the variable and instead change the netsuite_data_model variable to fit your configuration needs.

(Optional) Step 7: Orchestrate your models with Fivetran Transformations for dbt Core™

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.

Does this package have dependencies?

This dbt package is dependent on the following dbt packages. 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.yml file, we highly recommend that you remove them from your root packages.yml to 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"]

    - package: dbt-labs/spark_utils
      version: [">=0.3.0", "<0.4.0"]

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 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.

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. Check out this dbt Discourse article to learn how to contribute to a dbt package.

Are there any resources available?

  • If you have questions or want to reach out for help, see 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.