Payables Selected Installments Report

Payables◆ Seeded · Payments

Lists invoice installments selected in a payment process request, to assess how well the selection criteria pick the right invoices.

Sample build of the Payables Selected Installments 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

1,240

Selected installments

$12.00M

Selected

Wrongly excluded

Supplier	Invoice	Installment	Due Date	Selected Amount	Discount
Acme Industrial	Sample	Sample	2026-04-30	$1,240,500.00	Sample
Northwind Trading	—	—	2026-03-31	$842,150.75	—
Globex Holdings	Sample	Sample	2026-02-28	$96,400.00	Sample
Initech LLC	—	—	2026-01-31	$1,005,233.10	—
Umbrella Corp	Sample	Sample	2025-12-31	$58,720.40	Sample
Acme Industrial	Sample	Sample	2026-04-30	$1,240,500.00	Sample

AI Analyst · active

reading

The report lists invoice installments selected in a payment process request to assess the selection criteria.

flag

18 due installments were excluded from the run — invoices that should be paid this cycle won't be.

root cause & next step

Check the request's selection criteria such as pay-through date and pay groups; installments wrongly excluded become next week's past-due.

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_INVOICES_ALL	dimension	dimension
IBY_PAYMENTS_ALL	dimension	dimension
Selected 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_PAYMENT_SCHEDULES_ALL	21	2
AP_INVOICES_ALL	63	15
IBY_PAYMENTS_ALL	Setup / configuration table — joined for reference, not exposed for analytics

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 Used to tune pay-run criteria; usually extended with a what-if of cash impact per selection rule. Irvine rebuilds these on your data.