Glossary

Quarterly Services Survey

Quarterly Services Survey is (QSS) is the Census Bureau's quarterly revenue survey of service industries; Census Bureau Economic Indicators Briefing Room records "temporal:". In Datadory's catalog of 1,744 datasets, Census Bureau Economic Indicators Briefing Room and service-annual-survey-quarterly-services-survey are working examples.

What is Quarterly Services Survey?

The Quarterly Services Survey (QSS) is the Census Bureau's quarterly revenue survey of service industries, running from roughly 2004 to present.

For this industry it matters because its detailed kind-of-business tables report traveler accommodation (NAICS 721) revenue — the series this catalog tags as a RevPAR proxy.

In this catalog it appears concretely: - Census Bureau Economic Indicators Briefing Room — "temporal:". - service-annual-survey-quarterly-services-survey — "QSS: quarterly, rolling history back to the survey".

Why does Quarterly Services Survey matter when choosing a dataset?

A label on a listing is not a deliverable. Teams that license on the strength of a product-name match routinely find the shipped files cover a narrower slice than they assumed, and backfilling history afterwards costs more than the license ever did.

The failure mode is concrete: the label appears in a listing, the delivered files tell a different story, and the gap surfaces mid-project when fixing it is most expensive.

You rarely have to take a vendor's word for it. 82.4% of the 1,744 datasets Datadory catalogs are free to access, and Census Bureau Economic Indicators Briefing Room lets you inspect the real artifact before any budget is committed.

How do you evaluate Quarterly Services Survey in a data source?

Treat every claim of this attribute as testable:

  1. Open Census Bureau Economic Indicators Briefing Room and confirm its record — "temporal:" — against the files you actually receive.
  2. Open service-annual-survey-quarterly-services-survey and confirm its record — "QSS: quarterly, rolling history back to the survey" — against the files you actually receive.
  3. Pin down update cadence in writing. Across this catalog, 22.6% of 1,744 datasets refresh daily and 64 still arrive only through a manual request form, so ask exactly how fresh each release is.
  4. Check whether definitions are verified at all. Field definitions are verified for 1495 of 1,744 datasets (85.7%), and any source you license should meet that bar.
  5. Price the delivery route before the license. In this catalog bulk download is the most common access method (725 datasets) ahead of official APIs (574), and 379 sources still require scraping — a maintenance cost that lands on you, not the vendor.

See the term applied to real records: hotel-resort-reits data, research-consulting-services data.

Adjacent concepts worth reading next: - annual business survey - NAICS Classification - revpar - traveler accommodations

Frequently asked questions

What is an example of Quarterly Services Survey?

Census Bureau Economic Indicators Briefing Room is the clearest example in this catalog. Its record states: "temporal:". Across all 1,744 datasets Datadory averages a quality score of 7.81 out of 10, so a named example can be weighed rather than trusted blindly.

Is data described as "Quarterly Services Survey" free to use?

Treat access and permission separately. 82.4% of the 1,744 datasets in this catalog are free to access, but 235 are freemium and 61 are paid outright, so confirm both the price and the license on the exact distribution before building on it.

How do I verify a source really provides Quarterly Services Survey?

Open Census Bureau Economic Indicators Briefing Room next to service-annual-survey-quarterly-services-survey and compare the promise with the download. Field definitions are verified for 1495 of 1,744 datasets (85.7%), which makes that check fast inside the catalog and manual outside it.

Datasets containing this field

Datasets containing Quarterly Services Survey

6 datasets carry quarterly services survey in the catalog. Open one, count the fields, judge for yourself.

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