Total Obligated Amount
Numeric amount the contract record reports as the total obligated dollars. It represents the cumulative obligated funding captured in the FPDS award record at the time of reporting.
FPDS Compare
Use Cases
- Dictionary lookup and field explanation
- SQL filtering and grouping
- Analytical reporting and reusable query building
- Spending aggregation and trend analysis
Common Usage
- Obligation totals by agency, vendor, or fiscal year
- Award value ranking and market sizing
- Filtering high-dollar awards for review or segmentation
Common Mistakes
- Confusing obligated amount with ceiling, estimated value, or awarded amount
- Summing multiple award versions or modifications without deduplication
Query Guidance
Use the field as a numeric measure in SELECT, SUM, AVG, and threshold filters, and group it only at the award grain or a deduplicated snapshot grain. Apply null handling and check for amendments or multiple reporting versions before aggregating; for SQL, prefer SUM(COALESCE(content__award__totalDollarValues__totalObligatedAmount,0)) with a clearly defined DISTINCT or latest-record logic when needed.
SQL Examples
Preview values
SELECT
content__award__totalDollarValues__totalObligatedAmount AS total_obligated_amount
FROM fpds.data
WHERE content__award__totalDollarValues__totalObligatedAmount IS NOT NULL
LIMIT 25
Aggregate total
SELECT
sum(content__award__totalDollarValues__totalObligatedAmount) AS total_value
FROM fpds.data
WHERE content__award__totalDollarValues__totalObligatedAmount IS NOT NULL
Distribution overview
SELECT
min(content__award__totalDollarValues__totalObligatedAmount) AS min_value,
avg(content__award__totalDollarValues__totalObligatedAmount) AS avg_value,
max(content__award__totalDollarValues__totalObligatedAmount) AS max_value,
count() AS record_count
FROM fpds.data
WHERE content__award__totalDollarValues__totalObligatedAmount IS NOT NULL
Each dictionary item includes SQL-ready examples generated alongside the variable metadata, allowing immediate use in FPDS Query for filtering, aggregation, and analysis.