Asset Additions by Cost Center Report

Fixed Assets◆ Seeded · Additions

Assets added or capitalized in a period sorted and totaled by cost center, balancing segment, asset type, and account.

Sample build of the Asset Additions by Cost Center 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

Cost centers

$8.40M

Added cost

No cost center

Cost Center	Asset Type	Asset	Cost	Cost Account
$1,240,500.00	Standard	Sample	$1,240,500.00	$1,240,500.00
$842,150.75	Corporate	—	$842,150.75	$842,150.75
$96,400.00	Standard	Sample	$96,400.00	$96,400.00
$1,005,233.10	Default	—	$1,005,233.10	$1,005,233.10
$58,720.40	Standard	Sample	$58,720.40	$58,720.40
$1,240,500.00	Standard	Sample	$1,240,500.00	$1,240,500.00

AI Analyst · active

reading

The report totals additions by cost center, asset type, and account.

flag

Three additions hit no cost center, so they can't be reported in any cost-center capital roll-up.

root cause & next step

Assign cost centers; an addition with no cost center is invisible to the budget owners who fund it.

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_DISTRIBUTION_HISTORY	dimension	dimension
FA_BOOKS	dimension	dimension
Cost Center	measure	measure
Cost	measure	measure
Cost Account	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_ADDITIONS_B	15	9
FA_DISTRIBUTION_HISTORY	6	2
FA_BOOKS	20	2

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 Usually a parameter on a single additions view rather than a separate report. Irvine rebuilds these on your data.