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dollar Finance πŸ›οΈ Houston Finance Department aging

Houston City Spending & Checkbook

City payments to vendors by department, fund, and category for financial transparency.

πŸ—‚οΈ
300
Records
🚩
16
Red flags
βœ…
83
Quality score
πŸ”„
monthly
Update frequency

Data Detective

Tip

Scan the map for red dots and check the chart for spikes. Big jumps or drops are usually where the interesting questions live.

Source: The numbers above come straight from Houston Open Data.

πŸ“ Data quality breakdown

How healthy is this dataset across five dimensions?

Completeness 94/100
Freshness 40/100
Location 99/100
Consistency 93/100
Usefulness 85/100

πŸ—ΊοΈ Where the data lives

Up to 300 geolocated records. Red markers are flagged values.

πŸ“ˆ Activity over time

Record volume by month, or by status when no dates exist.

🚩 Open red flags

Suspicious values our scanner caught β€” see if you agree.

🚩 High · future date
95% sure

This record is dated in the future.

occurred_at 2026-08-21
A 311 request can't be created next year. A future date usually means someone typed the date wrong or a computer formatted it incorrectly.

Next step: Check for a typo or a time-zone/format bug at the source.

🚩 High · future date
95% sure

This record is dated in the future.

occurred_at 2026-08-16
A 311 request can't be created next year. A future date usually means someone typed the date wrong or a computer formatted it incorrectly.

Next step: Check for a typo or a time-zone/format bug at the source.

🚩 High · future date
95% sure

This record is dated in the future.

occurred_at 2026-08-16
A 311 request can't be created next year. A future date usually means someone typed the date wrong or a computer formatted it incorrectly.

Next step: Check for a typo or a time-zone/format bug at the source.

🚩 High · impossible negative
85% sure

A count or amount is negative where that should be impossible.

numeric_value -2
You can't have negative days to fix a pothole, or negative permits. A negative number here is a sign of a data-entry or calculation mistake.

Next step: Confirm whether negatives represent refunds/corrections or are simply errors.

🚩 High · impossible negative
85% sure

A count or amount is negative where that should be impossible.

numeric_value -30
You can't have negative days to fix a pothole, or negative permits. A negative number here is a sign of a data-entry or calculation mistake.

Next step: Confirm whether negatives represent refunds/corrections or are simply errors.

🚩 High · impossible negative
85% sure

A count or amount is negative where that should be impossible.

numeric_value -1
You can't have negative days to fix a pothole, or negative permits. A negative number here is a sign of a data-entry or calculation mistake.

Next step: Confirm whether negatives represent refunds/corrections or are simply errors.

🚩 High · totals mismatch
85% sure

The published total (0) does not match the number of detail rows (300).

record_count declared 0 vs 300 rows
If a report says 1,000 service requests but only 900 rows exist, 100 are missing or the headline number is wrong. Either way the public is getting a number that doesn't add up.

Next step: Reconcile the summary total against the detailed records.

🚩 High · stale dataset
80% sure

Expected updates every monthly, but it has been 135 days, 12 hours.

last_source_update 2026-03-20
A dataset that's supposed to refresh monthly but hasn't in 135 days, 12 hours is like a bus schedule nobody updated β€” you can't trust it to reflect what's happening now.

Next step: Ask the department whether updates stopped or moved elsewhere.

⚠️ Known issues

  • β€’Vendor names inconsistent
  • β€’Some amounts appear as negatives (refunds)

πŸ’‘ Public use cases

  • β€’Follow city spending
  • β€’See top vendors
  • β€’Check whether totals add up

πŸ“ Geo fields

No geo fields mapped.

πŸ•’ Time fields

payment_date

Records: 300

Update frequency: monthly

Last imported: 1 hour ago

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