Sage Intacct (Source)

This package models Sage Intacct 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 column-level testing where applicable. For example, all ID fields are tested for non-null values.
• Models staging tables, which will be used in our transform package

Compatibility

Please be aware that the dbt_sage_intacct and dbt_sage_intacct_source packages were developed with single-currency company data. As such, the package models will not reflect accurate totals if your account has multi-currency enabled. If multi-currency functionality is desired, we welcome discussion to support this in a future version.

Models

This package contains staging models, designed to work simultaneously with our Sage Intacct transform package. The staging models are designed to:

• 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.
  • ID primary keys are prefixed with the name of the table. For example, the gl_detail table's recordno column is renamed gl_detail_id.
  • Foreign keys include the table that they refer to. For example, ap_bill_item's recordkey is named bill_id.

Installation Instructions

Add the following configuration to your packages.yml file:

# packages.yml
packages:
  - package: fivetran/sage_intacct_source
    version: [">=0.1.0", "<0.2.0"]

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

Configuration

By default, this package looks for your Sage Intacct data in the sage_intacct schema of your target database. If this is not where your Sage Intacct data is, add the following configuration to your dbt_project.yml file:

# dbt_project.yml

...
config-version: 2

vars:
    sage_intacct_database: your_database_name
    sage_intacct_schema: your_schema_name 

Passthrough Columns

This package allows users to add additional columns to the stg_sage_intacct__gl_account table. Columns passed through must be present in the upstream source tables. See below for an example of how the passthrough columns should be configured within your dbt_project.yml file.

# dbt_project.yml

...
vars:
  sage_intacct_source:
    sage_account_pass_through_columns: ['new_custom_field', 'custom_field_2']

Disabling and Enabling Models

When setting up your Sage Intacct Source (Sage) connection in Fivetran, it is possible that not every table this package expects will be synced. This can occur because you either don't use that functionality in Sage or have actively decided to not sync some tables. In order to disable the relevant functionality in the package, you will need to add the relevant variables.

By default, all variables are assumed to be true. You only need to add variables for the tables you would like to disable:

# dbt_project.yml

config-version: 2

vars:
    sage_intacct__using_invoices: false                 # default is true

Change the Build Schema

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

# dbt_project.yml

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

Contributions

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 Support

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

Databricks Dispatch Configuration

dbt v0.20.0 introduced a new project-level dispatch configuration that enables an "override" setting for all dispatched macros. If you are using a Databricks destination with this package, you need to add the dispatch configuration below (or a variation of that 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.

# dbt_project.yml

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

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
• 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
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