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QRFY model

Scans by location and device

Where and on what devices codes are scanned: QRFY's country, city and operating-system breakdowns, per code per month.

See the SQLAll QRFY models
Grain
one row per month (UTC) x QR code (scan_url) x country x city x operating system
Built from
  1. 1
    Raw tables
  2. 1
    Staging
  3. 1
    Core
  4. 1
    Analytics
Reads from QRFY
analytics
Ships as
Weld and dbt SQL, open source on GitHub
core.qrfy.scans_by_location_and_device
1-- core.qrfy.scans_by_location_and_device
2-- Where and on what devices codes are scanned: QRFY's country, city and operating-system
3-- breakdowns, per code per month.
4--
5-- Grain: one row per month (UTC) x QR code (scan_url) x country x city x operating system.
6-- Depends on: staging.qrfy.analytics
7--
8-- Location is QRFY's IP-based estimate, so city is approximate and can be empty. OS
9-- version is left out of the grain to keep rows readable; it is on the staging model if
10-- you need it.
11
12SELECT
13    DATE_TRUNC(DATE(scanned_at), MONTH)                         AS month,
14    scan_url,
15    country_iso,
16    country,
17    city,
18    os,
19    COUNT(*)                                                    AS scans,
20    COUNTIF(is_unique_visitor)                                  AS unique_scans
21FROM {{staging.qrfy.analytics}}
22GROUP BY 1, 2, 3, 4, 5, 6

This model and the 2 it depends on. Deploy them together; refs like {{staging.…}} resolve to the matching folders in Weld, and the dbt view uses source() and ref().

Notes

How it counts. And where it stops.

Location is QRFY's IP-based estimate, so city is approximate and can be empty. OS version is left out of the grain to keep rows readable; it is on the staging model if you need it.

Raw tables it reads

  • raw.qrfy.analytics

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