Import AutoInvoice Execution Report

Receivables◆ Seeded · Billing

Reports the outcome of the AutoInvoice import that brings transactions from external systems into Receivables, listing successful and rejected records by transaction type, customer, transaction number, and date.

Sample build of the Import AutoInvoice Execution 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

12,400

Lines imported

240

Rejected

$380K

Held revenue

Batch	Lines Imported	Lines Rejected	Amount	Error Reason
Sample	Sample	Sample	$1,240,500.00	Standard
—	—	—	$842,150.75	Corporate
Sample	Sample	Sample	$96,400.00	Standard
—	—	—	$1,005,233.10	Default
Sample	Sample	Sample	$58,720.40	Standard
Sample	Sample	Sample	$1,240,500.00	Standard

AI Analyst · active

reading

The report reports the AutoInvoice run — lines imported versus rejected from external systems.

flag

240 lines were rejected, holding $380K of revenue in the interface, not yet invoiced or recognized.

root cause & next step

Fix the interface errors — usually missing customer, item, or tax setup; a rejected AutoInvoice line is a sale that never became an invoice.

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

RA_INTERFACE_LINES_ALL
RA_INTERFACE_ERRORS_ALL
RA_CUSTOMER_TRX_ALL

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
RA_INTERFACE_ERRORS_ALL	dimension	dimension
RA_CUSTOMER_TRX_ALL	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.

Receivables 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
RA_INTERFACE_LINES_ALL	Setup / configuration table — joined for reference, not exposed for analytics
RA_INTERFACE_ERRORS_ALL	Setup / configuration table — joined for reference, not exposed for analytics
RA_CUSTOMER_TRX_ALL	58	16

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 The rejection listing is hard to action; the common build groups errors by reason and feeds a correction queue rather than a flat log. Irvine rebuilds these on your data.