Sage Intacct dbt Package (Docs)

What does this dbt package do?

• Produces modeled tables that leverage Sage Intacct data from Fivetran's connector in the format described by this ERD.

The main focus of this package is to provide users with insights into their Sage Intacct data that can be used for financial reporting and analysis. This is achieved by the following:

• Creating the general ledger, balance sheet, and profile & loss statement on a month by month grain
• Creating an enhanced AR and AP model

Compatibility

Please be aware that the dbt_sage_intacct package was 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.

The following table provides a detailed list of all tables materialized within this package by default.

Materialized Models

Each Quickstart transformation job run materializes 23 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.

How do I use the dbt package?

Step 1: Prerequisites

To use this dbt package, you must have the following:

• At least one Fivetran Sage Intacct connection syncing data into your destination.
• A BigQuery, Snowflake, Redshift, PostgreSQL, or Databricks destination.

Databricks Dispatch Configuration

If you are using a Databricks destination with this package you will need to add the below (or a variation of the below) 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

Include the following sage_intacct 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/sage_intacct
    version: [">=1.1.0", "<1.2.0"] # we recommend using ranges to capture non-breaking changes automatically

All required sources and staging models are now bundled into this transformation package. Do not include fivetran/sage_intacct_source in your packages.yml since this package has been deprecated.

Step 3: Define database and schema variables

Option A: Single connection

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

vars:
  sage_intacct:
    sage_intacct_database: your_database_name
    sage_intacct_schema: your_schema_name

Option B: Union multiple connections

If you have multiple Sage Intacct connections in Fivetran and would like to use this package on all of them simultaneously, we have provided functionality to do so. For each source table, the package will union all of the data together and pass the unioned table into the transformations. The source_relation column in each model indicates the origin of each record.

To use this functionality, you will need to set the sage_intacct_sources variable in your root dbt_project.yml file:

# dbt_project.yml

vars:
  sage_intacct:
    sage_intacct_sources:
      - database: connection_1_destination_name # Required
        schema: connection_1_schema_name # Required
        name: connection_1_source_name # Required only if following the step in the following subsection

      - database: connection_2_destination_name
        schema: connection_2_schema_name
        name: connection_2_source_name

Recommended: Incorporate unioned sources into DAG

If you are running the package through Fivetran Transformations for dbt Core™, the below step is necessary in order to synchronize model runs with your Sage Intacct connections. Alternatively, you may choose to run the package through Fivetran Quickstart, which would create separate sets of models for each Sage Intacct source rather than one set of unioned models.

By default, this package defines one single-connection source, called sage_intacct, which will be disabled if you are unioning multiple connections. This means that your DAG will not include your Sage Intacct sources, though the package will run successfully.

To properly incorporate all of your Sage Intacct connections into your project's DAG:

1. Define each of your sources in a .yml file in your project. Utilize the following template for the source-level configurations, and, most importantly, copy and paste the table and column-level definitions from the package's src_sage_intacct.yml file.

# a .yml file in your root project

version: 2

sources:
  - name: <name> # ex: Should match name in sage_intacct_sources
    schema: <schema_name>
    database: <database_name>
    loader: fivetran
    config:
      loaded_at_field: _fivetran_synced
      freshness: # feel free to adjust to your liking
        warn_after: {count: 72, period: hour}
        error_after: {count: 168, period: hour}

    tables: # copy and paste from sage_intacct/models/staging/src_sage_intacct.yml - see https://support.atlassian.com/bitbucket-cloud/docs/yaml-anchors/ for how to use anchors to only do so once

Note: If there are source tables you do not have (see Step 4), you may still include them, as long as you have set the right variables to False.

2. Set the has_defined_sources variable (scoped to the sage_intacct package) to True, like such:

# dbt_project.yml
vars:
  sage_intacct:
    has_defined_sources: true

(Optional) Step 4: Additional configurations

Passthrough Columns

This package allows users to add additional columns to the stg_sage_intacct__gl_account and stg_sage_intacct__gl_detail 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_account_pass_through_columns: ['new_custom_field', 'custom_field_2']
  sage_gl_pass_through_columns: ['custom_field_3', 'custom_field_4']

Custom Account Classification

Accounts roll up into different accounting classes based on their category. The categories are brought in from the gl_account table. We created a variable for each accounting class (Asset, Liability, Equity, Revenue, Expense) that can be modified to include different categories based on your business. You can modify the variables within your root dbt_project.yml file. The default values for the respective classes are as follows:

# dbt_project.yml

vars:
    sage_intacct_category_asset: ('Inventory','Fixed Assets','Other Current Assets','Cash and Cash Equivalents','Intercompany Receivable','Accounts Receivable','Deposits and Prepayments','Goodwill','Intangible Assets','Short-Term Investments','Inventory','Accumulated Depreciation','Other Assets','Unrealized Currency Gain/Loss','Patents','Investment in Subsidiary','Escrows and Reserves','Long Term Investments')
    sage_intacct_category_equity: ('Partners Equity','Retained Earnings','Dividend Paid')
    sage_intacct_category_expense: ('Advertising and Promotion Expense','Other Operating Expense','Cost of Sales Revenue', 'Professional Services Expense','Cost of Services Revenue','Payroll Expense','Payroll Taxes','Travel Expense','Cost of Goods Sold','Other Expenses','Compensation Expense','Federal Tax','Depreciation Expense')
    sage_intacct_category_liability: ('Accounts Payable','Other Current Liabilities','Accrued Liabilities','Note Payable - Current','Deferred Taxes Liabilities - Long Term','Note Payable - Long Term','Other Liabilities','Deferred Revenue - Current')
    sage_intacct_category_revenue: ('Revenue','Revenue - Sales','Dividend Income','Revenue - Other','Other Income','Revenue - Services','Revenue - Products')

Disabling and Enabling Models

When setting up your Sage Intacct (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
    sage_intacct__using_bills: false                    # default is true

Changing the Build Schema

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

# dbt_project.yml 

models:
    sage_intacct:
      +schema: my_new_schema_name # Leave +schema: blank to use the default target_schema.
      staging:
        +schema: my_new_schema_name # Leave +schema: blank to use the default 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:
    sage_intacct_<default_source_table_name>_identifier: your_table_name 

(Optional) Step 5: Orchestrate your models with Fivetran Transformations for dbt Core™

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 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 on the best workflow for contributing to a 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.