Payables Unaccounted Transactions and Sweep Report

Payables◆ Seeded · Period close

Lists invoices and payments that weren't accounted for a period or date range.

Sample build of the Payables Unaccounted Transactions and Sweep Report — reconciled, and rendered tool-neutral so it runs in Power BI, ThoughtSpot, or Tableau.

Sample build · illustrative

Filters

Period

FEB-26

Ledger

US Primary

Currency

USD

Unaccounted

$1.40M

Unaccounted value

To sweep

Transaction	Type	Supplier	Amount	Accounting Status	Action
Sample	Standard	Acme Industrial	$1,240,500.00	Open	Sample
—	Corporate	Northwind Trading	$842,150.75	Posted	—
Sample	Standard	Globex Holdings	$96,400.00	Validated	Sample
—	Default	Initech LLC	$1,005,233.10	Open	—
Sample	Standard	Umbrella Corp	$58,720.40	Paid	Sample
Sample	Standard	Acme Industrial	$1,240,500.00	Open	Sample

AI Analyst · active

reading

The report lists invoices and payments not accounted for the period, with the sweep option.

flag

$1.4M is unaccounted at the period cut; 22 will sweep to the next period — accounting deferred, not resolved.

root cause & next step

Account what can be accounted and sweep only true exceptions; sweeping to avoid fixing an error just moves the problem forward.

Illustrative data. The live interactive version — drill-through, filters, export, and the AI Analyst — runs on your warehouse. See it live →

This is the report's BI Publisher data model — the SQL data set BI Publisher runs against Oracle tables to produce the output. The same SQL becomes a dbt model in your warehouse, so one definition drives both the formatted report and the analytics layer.

Data sources

How it interconnects: this data set reads the physical tables above. Those same tables surface in OTBI as subject areas and in BICC as PVOs — three lenses on one source. Open any table to trace its subject areas and View Objects.

The SQL data set is authored to this report's exact spec during the build and ships as the BI Publisher data model plus a matching dbt model — one definition, both layers.

The data-warehouse model — one fact surrounded by conformed dimensions (what you slice by) and measures (what you aggregate), expressed as dbt so it migrates with you. Grain: one row per source transaction.

●— fact → dimension join

Element	Type	Definition
AP_INVOICE_PAYMENTS_ALL	dimension	dimension
XLA_EVENTS	dimension	dimension
Amount	measure	measure

Runs on your cloud warehouse — Snowflake, BigQuery, Redshift, or Synapse on AWS, Google Cloud, Azure, or any provider. Reconciled to the source control total — 0% variance by design. You own the code, the model, and the data.

How the data gets here: a BICC bulk extract of the source tables above, on the same pattern for every report. See the extraction pattern & data flow →

See the complete model

How this report's fact and dimensions fit the full picture, via conformed keys.

Payables data model →Enterprise model →

Every source object behind this report. Each linked table has its own page with full column descriptions, drawn from the Oracle BICC lineage and articulated for practitioners.

Table	Reporting columns	Subject areas
AP_INVOICES_ALL	63	15
AP_INVOICE_PAYMENTS_ALL	22	2
XLA_EVENTS	3	1

Reporting columns = fields the report selects that are exposed as analytics attributes; subject areas = the OTBI subject areas the table appears in. Setup and configuration tables (master data, ledger and book setup, lookups) are referenced by the report's joins but aren't exposed as analytics columns or subject areas — that's expected, not a gap.

Customization note A close blocker; teams rebuild it as a daily unaccounted-transactions monitor instead of a period-end surprise. Irvine rebuilds these on your data.