Adobe Analytics Account Usage Logs: A Checklist of Surprises & Should-Knows

Two Adobe Analytics admins discussing whether to raise the entry bar for their trainings for advanced users.

The List of Should-Knows and Surprises

Me trying to figure out the different values for different languages…
# Removes \xa0 characters that are found in the logs in various languages  
logs_df['eventDescription'] = logs_df['eventDescription'].str.split().str.join(' ')
# The example assumes we have a logs extract that contains only logs of type 2 (logins) or 23 (Workspace Events)# Extract the Raw Event Name from the eventDescription
en = logs_df["eventDescription"].str.extract('(^[\w ]+)($|: | \- )', expand=True)
logs_df["eventName_raw"] = en[0].str.strip()
# Map to normalized Event Names
view_variants = ['Project Viewed', 'Angezeigtes Projekt', 'Projet affiché', 'Proyecto visualizado']
create_variants = ['Project Created', 'Projekt erstellt', 'Projet créé', 'Proyecto creado']

def do_map(row):
if row["eventType"] == 2: # logins can be simply recognized by eventType 2
return "login"
if row["eventName_raw"] in view_variants:
return "project_view"
if row["eventName_raw"] in create_variants:
return "project_create"
return ""
# generate the normalized event name
logs_df["eventName"] = logs_df.apply(do_map, axis=1)
# Filtering out create and view events
logs_df = logs_df[logs_df["eventName"] != ""]
regex = re.compile("=([a-z0-9]{24})( |$)")  # project IDs are always 24-char hashes

pid = logs_df["eventDescription"].str.extract(regex, expand=True)
logs_df["projectId"] = pid[0]
logs_df["projectId"] = logs_df["projectId"].fillna("")
While the logs are saying this project was created on Jan 24 2022, …
… the Workspace (projects) API and interface show Jun 26 2021 as the create date.

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