from Jeff Klukas
Originally published as a cookbook on docs.telemetry.mozilla.org to instruct data users within Mozilla how to take advantage of the usage history stored in our BigQuery tables.
Monthly active users (MAU) is a windowed metric that requires joining data
per client across 28 days. Calculating this from individual pings or daily
aggregations can be computationally expensive, which motivated creation of the
clients_last_seen dataset
for desktop Firefox and similar datasets for other applications.
A powerful feature of the clients_last_seen methodology is that it doesn’t
record specific metrics like MAU and WAU directly, but rather each row stores
a history of the discrete days on which a client was active in the past 28 days.
We could calculate active users in a 10 day or 25 day window just as efficiently
as a 7 day (WAU) or 28 day (MAU) window. But we can also define completely new
metrics based on these usage histories, such as various retention definitions.