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Vibedata

Build something that is not there yet

Build occupancy, ADR, and RevPAR by property and day

  • When revenue management pulls occupancy and RevPAR nightly and the numbers don't match finance's month-end figures.
  • When out-of-order rooms and complimentary stays get handled differently depending on who built the report.

Build rooms sold, rooms available, and room revenue per property and day, and derive occupancy, ADR, and RevPAR. Covers these three measures, not broader revenue management forecasting.

Area
Transformation
Runs on
  • Microsoft Fabric Lakehouse
  • Microsoft Fabric Warehouse
  • MotherDuck
  • DuckDB
Built with
  • dbt
Industry
Hospitality
Readiness
SupportedEverything this Recipe composes runs today, without a case that proves this exact shape.
Before you start
needs an agreed out-of-order and complimentary-stay rule

Sample This Recipe has not been materialized in the Cookbook repository yet. Its trigger, description, prompt, agent guidance and acceptance conditions, and the explanation below, are prototype drafts. Its name, job, area and readiness come from the reconciled Cookbook seed snapshot. Readiness is a separate question from this one: it says whether the capability exists, not whether the writing has been reviewed.

Use this Recipe

Use the VibeData Recipe `hospitality-occupancy-adr-revpar` at https://getvibedata.ai/cookbook/hospitality-occupancy-adr-revpar Read the Recipe and execute it in the context of the current Intent.

Recipe id hospitality-occupancy-adr-revpar · Not yet materialized in the Cookbook repository, so the pointer addresses this page.

Verified by

What has to be observably true before this Recipe is finished.

  • rooms sold never exceeds rooms available for any property-day
  • out-of-order rooms and complimentary stays are handled per the one agreed rule everywhere they appear
  • a reproduced property-month's RevPAR matches finance's previously reported figure
  • revenue components, whether room only or room plus fees, are applied consistently across properties
Recipe promptThe task specification the agent reads. Reference only — it is not what you copy.
Deliver: Build occupancy, ADR, and RevPAR by property and day.

Build rooms sold, rooms available, and room revenue per property and day, and derive occupancy, ADR, and RevPAR. Covers these three measures, not broader revenue management forecasting.

Execute inside the current Intent. Its Domain, repository, platform, environment and attached sources are the context for this work — read them rather than asking for them.

The work is done when:
- rooms sold never exceeds rooms available for any property-day
- out-of-order rooms and complimentary stays are handled per the one agreed rule everywhere they appear
- a reproduced property-month's RevPAR matches finance's previously reported figure
- revenue components, whether room only or room plus fees, are applied consistently across properties

Report the evidence for each condition above with the result. A condition you cannot meet is something to say, not something to work around.
Agent guidanceHow the agent approaches the work, and what it will not do.

Profile the inputs the grain, joins and measures actually depend on before proposing a model. Put the design up for review — grain first — then build in an isolated copy with tests and documentation landing beside the model rather than after it.

Composes

  • dbt model authoring and layering
  • dbt in the project
  • isolated-copy execution and gate verification

Asks first

Semantic decisions the Intent cannot supply. Never context Studio already holds.

  • which Fabric target this work lands on, when the Domain carries both a Lakehouse and a Warehouse

Guardrails

  • Build in an isolated copy. Production is read, never written.

What you need

  • Microsoft Fabric Lakehouse, Microsoft Fabric Warehouse, MotherDuck, or DuckDB.
  • A dbt project you can build, and read access to the models it starts from.
  • dbt in the project, or the intent to add it.
  • Needs an agreed out-of-order and complimentary-stay rule.

How it goes

  1. State the outcome in one sentence, in the language the request arrived in.
  2. Let it profile the inputs the grain, the joins and the measures actually depend on.
  3. Review the design. Disagreeing about grain here costs a sentence; after the model exists it costs a rewrite.
  4. Let it build in an isolated copy, with the tests and the documentation landing beside the model rather than after it.
  5. Read the acceptance conditions against the run.

What you end up with

The deliverable, in your own repository, as transformation work a reviewer who knows the project reads as native to it. Alongside it, the evidence for every one of the acceptance conditions above — which is the part that is still there in three weeks when somebody asks.