Mass Additions Report

Fixed Assets◆ Seeded · Additions

Mass addition lines brought in from Payables and Projects waiting to post to Assets, with their queue status, so finance can review and prepare them before posting.

Sample build of the Mass Additions 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

210

Lines in queue

$4.60M

Queued cost

Incomplete

Mass Addition	Source	Cost	Queue Status	Category	Cost Center
Sample	Sample	$1,240,500.00	Open	Computer-Hardware	$1,240,500.00
—	—	$842,150.75	Posted	Buildings	$842,150.75
Sample	Sample	$96,400.00	Validated	Vehicles	$96,400.00
—	—	$1,005,233.10	Open	Furniture-Fixtures	$1,005,233.10
Sample	Sample	$58,720.40	Paid	Machinery	$58,720.40
Sample	Sample	$1,240,500.00	Open	Computer-Hardware	$1,240,500.00

AI Analyst · active

reading

The report lists mass addition lines from Payables and Projects waiting to post, with their queue status.

flag

28 lines are incomplete — missing category, cost center, or in-service date — and can't post until fixed.

root cause & next step

Complete the 28 before the depreciation run; an incomplete mass-addition line is capital stuck outside the asset register.

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
FA_ADDITIONS_B	dimension	dimension
AP_INVOICE_DISTRIBUTIONS_ALL	dimension	dimension
Cost	measure	measure
Cost Center	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.

Fixed Assets 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
FA_MASS_ADDITIONS	Setup / configuration table — joined for reference, not exposed for analytics
FA_ADDITIONS_B	15	9
AP_INVOICE_DISTRIBUTIONS_ALL	59	11

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 Rebuilt as a prepare-mass-additions workbench that flags lines missing category, cost center, or in-service date. Irvine rebuilds these on your data.