Sage Intacct dbt Package

This dbt package transforms data from Fivetran's Sage Intacct connector into analytics-ready tables.

Resources

Number of materialized models¹: 23
Connector documentation
- Sage Intacct connector documentation
- Sage Intacct ERD
dbt package documentation

What does this dbt package do?

This package enables you to create general ledger, balance sheet, and profit & loss statements by period and enhance AR and AP models. It creates enriched models with metrics focused on financial reporting and analysis.

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.

Output schema

Final output tables are generated in the following target schema:

<your_database>.<connector/schema_name>_sage_intacct

Final output tables

By default, this package materializes the following final tables:

Table	Description
sage_intacct__general_ledger	Tracks all financial transactions with offsetting debit and credit entries by account, category, and classification to provide a complete audit trail and transaction history. Example Analytics Questions: What is the total debit and credit activity by account and classification? Which accounts have the highest transaction volumes or largest balance changes? How do debits and credits balance across different categories and time periods?
sage_intacct__general_ledger_by_period	Summarizes account activity by period with beginning balances, ending balances, and net changes to track financial position over time and support financial statement preparation. Example Analytics Questions: What are the beginning and ending balances for each account by period? Which accounts show the largest net changes period-over-period? How do period-over-period balances trend by account category and classification?
sage_intacct__balance_sheet	Aggregates balance sheet transactions by period, account, category, and classification to track assets, liabilities, and equity over time. Example Analytics Questions: What is the total asset value versus total liability value for each reporting period? How have account balances changed across different balance sheet categories? What is the equity position by classification and time period?
sage_intacct__profit_and_loss	Summarizes revenue and expense transactions by period, account, category, and classification to analyze profitability and income statement performance. Example Analytics Questions: What are total revenues versus total expenses for each accounting period? Which expense accounts or categories are growing fastest? What is the net profit or loss by classification and time period?
sage_intacct__ap_ar_enhanced	Provides detailed accounts payable and receivable transaction data with bill/invoice information, due dates, customer and vendor details, and line item breakdowns. Example Analytics Questions: Which customers or vendors have the highest outstanding balances? Which bills and invoices are approaching their due dates? How do transaction volumes vary by department, location, or account?

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.

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.

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.

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.