Customer Account Status Report

Receivables◆ Seeded · Receivables balances

Lists each customer's open items and total balance due based on account status, in the specified ledger currency.

Sample build of the Customer Account Status 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

1,840

Customers

$24.00M

Open AR

On credit hold

Customer	Account Status	Open Items	Balance Due	Currency
Acme Industrial	Open	Sample	$1,240,500.00	USD
Northwind Trading	Posted	—	$842,150.75	USD
Globex Holdings	Validated	Sample	$96,400.00	USD
Initech LLC	Open	—	$1,005,233.10	USD
Umbrella Corp	Paid	Sample	$58,720.40	USD
Acme Industrial	Open	Sample	$1,240,500.00	USD

AI Analyst · active

reading

The report lists each customer's open items and total balance due by account status.

flag

32 customers are on credit hold yet still carry shippable orders elsewhere — the hold isn't enforced end to end.

root cause & next step

Confirm credit-hold enforcement flows to order management; a hold AR sees but shipping doesn't is a credit-risk leak.

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
HZ_CUST_ACCOUNTS	dimension	dimension
HZ_PARTIES	dimension	dimension
RA_CUSTOMER_TRX_ALL	dimension	dimension
Balance Due	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
AR_PAYMENT_SCHEDULES_ALL	32	6
HZ_CUST_ACCOUNTS	14	43
HZ_PARTIES	81	144
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 Commonly extended with credit-limit utilization and rolling DSO so collections can prioritize, not just read a list. Irvine rebuilds these on your data.