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Data & Analytics
Starter

Rate Data Checker

Validate, clean and inspect rate data before anyone makes a pricing decision with it.

Version
0.1 draft
Maintainer
RH-maintained
Sample data
Sample data planned
Support status
To be defined
Licence status
To be defined

Inputs

What data is required?

  • Rate observations with pickup date, return date, pickup location, dropoff location and vehicle class
  • The currency each rate is quoted in
  • The timestamp the observation was collected
  • Optional: rate product or rate code, taxes, fees and length of rental

Outputs

What does it calculate, display or help you decide?

  • A validation report listing missing fields, duplicate observations, impossible date pairs and out-of-range values
  • A freshness summary showing how old each observation is at the moment you read it
  • A cleaned table you can export and reuse in other modules

Build prompt

Select the prompt below and paste it into your AI-assisted editor as a starting point, then change the field names so they match your own export.

Build a small web tool that loads a CSV of car rental rate observations. Each row has: observation_timestamp, pickup_location, dropoff_location, pickup_datetime, return_datetime, vehicle_class, rate_product, currency, base_rate, taxes, fees. Validate the file and show a report with: rows missing a required field; duplicate rows for the same location pair, date pair, vehicle class and rate product; rows where return_datetime is not after pickup_datetime; rows with a rental length outside 1 to 60 days; rows where base_rate is zero, negative or more than five times the median for that vehicle class; and rows where observation_timestamp is older than a freshness threshold I can set. Show the count and percentage for each issue, let me click an issue to see the affected rows, and let me export the cleaned rows as CSV. Do not change any value silently. Every exclusion must be visible and explained.

Sample data

Use synthetic rate observations or rate data you are authorised to use. Do not load live competitor feeds, customer records or nonpublic pricing into an early prototype.

Setup

  1. Create an empty project folder and open it in your AI-assisted editor.
  2. Paste the build prompt and let the assistant generate a first version.
  3. Point the tool at a small synthetic CSV, about 500 rows, so you can check the output by hand.
  4. Fix the field names so they match your own export.
  5. Set your freshness threshold in hours and re-run.

Dependencies

  • Any language or framework you are comfortable maintaining
  • A CSV parser
  • Nothing else is required for the first version. No connection to RateHighway services is needed.

Tests

  • Add a row with a return date before the pickup date. It must be flagged.
  • Duplicate an existing row exactly. The duplicate count must rise by one.
  • Change one observation timestamp to last week. It must appear as stale at a one day threshold.
  • Delete a currency value. The row must be flagged as missing a required field, not silently defaulted.
  • Confirm the exported row count equals input rows minus excluded rows.
Operating complication

The part that catches people out

Stale rates. A rate observation is only meaningful together with the moment it was collected. A competitor rate read eight hours ago may already have moved, and a file that mixes fresh and stale observations will quietly average them into a misleading picture.

Decide a freshness threshold before you read the numbers, show the age of every observation, and separate stale rows instead of dropping them without a trace. A tool that hides exclusions is harder to trust than one that shows a smaller, honest data set.

Optional

Optional RME connection

Where an operator already uses RateMonitor Elite, a supported RateHighway capability could in future supply rate observations through an approved interface instead of a manual export. Access, permissions and data rights for any such connection are not approved and would need to be defined first.

Any connection to RateHighway services would require approved interfaces, authorisation, tenant isolation and verified data rights. Nothing about access or availability is approved.

Build it, then check it by hand

Run the prompt, point it at sample data, and verify one row or one date against the source before you trust the whole file.

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