Metrics tables
Metrics tables contain aggregated tabular data. They combine data from fact, dimension, and bridge tables to provide an easy-to-use foundation for reports and dashboards.
The metric tables available are:
group_detail
This table aggregates activity information per user and day. It can help you build a flexible activity dashboard or report showing activity for the whole organization or per user for any period. Using only this table, for example, you can quickly create a dashboard like the one below:
user_id
The unique identifier of the user
date
The date for which the statistics are aggregated
total_hours_on_learn
Total time spent by the user on Learn content (assessments, courses, practices, and projects) on that date
total_hours_on_courses
Total time spent by the user on courses on that date
total_xp_earned
The amount of xp the user earned on the given date
nb_courses_started
The number of courses the user has started on the given date
nb_courses_completed
The number of courses the user has completed on the given date
nb_chapters_started
The number of chapters the user has started on the given date
nb_chapters_completed
The number of chapters the user has completed on the given date
nb_exercises_completed
The number of exercises the user has completed on the given date
nb_projects_started
The number of projects the user has started on the given date
nb_projects_completed
The number of projects the user has completed on the given date
nb_practices_completed
The number of practices the user has completed on the given date
nb_assessments_started
The number of assessments the user has started on the given date
nb_assessments_completed
The number of assessments the user has completed on the given date
nb_tracks_started
The number of tracks the user has started on the given date
nb_tracks_completed
The number of tracks the user has completed on the given date
nb_certifications_started
The number of certifications the user has completed on the given date
nb_certifications_completed
The number of certifications the user has completed on the given date
ai_tutor_hours_on_learn
Total time spent by the user on Learn AI Tutor content on that date
ai_tutor_hours_on_courses
Total time spent by the user on Learn AI Tutor courses on that date
ai_tutor_xp_earned
The amount of xp the user earned on the given date on AI Tutor content
ai_tutor_courses_started
The number of AI Tutor courses the user has started on the given date
ai_tutor_courses_completed
The number of AI Tutor courses the user has completed on the given date
user_engagement_detail
This table contains activity information per user at the content-item level. It tracks courses, course chapters, projects, and assessments.
This table shows users' activity for particular technologies, topics, or content items. When assigning content to users, it can help you determine who has done what, when they started, who has finished, and how much time they spent on a given set of content items.
user_id
The unique identifier of the user
content_id
The unique identifier of the content unit
course_variant_id
The course variant identifier. 1 = datacamp, 2 = ai-tutor. Can be joined with dim_course_variant for variant details.
content_title
The title of the content unit
started_at
The timestamp when the user started the content unit, if available
completed_at
The timestamp when the user completed the content unit, if available
hours_engaged
The number of hours the user spent on the content unit
xp_earned
The xp points the user earned on the content unit
pct_completed
The completion ratio (0-1.0) based on the xp earned
content_type
The content type of the content unit (course, chapter, project, assessment)
technology
The technology of the content unit
topic
The topic of the content unit
track_engagement_detail
This table contains information on the track activity for each user and each track they have enrolled in.
It is the companion to user_engagement_detail, but at the track level. Since tracks contain multiple items from different content types (courses, projects, assessments), a different metric table is needed to show the user's progress in the track and its constituent components.
The table shows who has started a track, who has completed it, and each user's detailed progress. It includes the number of courses, chapters, projects, and assessments in the track and the number each user has completed.
user_id
The unique identifier of the user
track_name
The name of the track
category
The category of the track (skills, career)
track_id
The unique identifier of the track
track_version_id
The unique identifier of the track version. A track can have multiple versions, all with the same track_id
is_custom
Whether or not a track is custom. If false, then the track is a regular (public) track
is_current_version
Whether or not the version of the track is the most recently published version
track_started_at
The timestamp when the user started the track.
track_completed_at
The timestamp when the user completed the track. If a user has not completed the track, this field is null
nb_courses
The number of courses that are part of the track
nb_courses_completed
The number of courses the user has completed in this track
nb_chapters
The number of chapters that are part of the track
nb_chapters_completed
The number of chapters the user has completed in this track
nb_projects
The number of projects that are part of the track
nb_projects_completed
The number of projects the user has completed in this track
nb_assessments
The number of assessments that are part of the track
nb_assessments_completed
The number of assessments the user has completed in this track
xp_available
The total XP available for the track
xp_earned
The XP the user has earned in the track
pct_xp_earned
The percentage of XP available the user has earned in this track
ai_tutor_credit_usage_detail
This table contains each learner's AI Tutor credit usage and current credit limit for the active 12-month reset window. It can help you monitor AI Tutor credit consumption, remaining credits, and users who have exceeded their current limit.
Each row represents one user in the group. Users with no AI Tutor course usage in the current reset window are included with credits_used_cum set to 0. If no AI Tutor credit limit is configured, limit-derived fields are null.
group_id
The unique identifier of the group
user_id
The unique identifier of the user
next_renewal_date
The active subscription term end date used to determine the current reset window
reset_window_start
The start date of the active 12-month reset window, inclusive
reset_window_end
The end date of the active 12-month reset window, exclusive
credits_used_cum
The number of AI Tutor credits used by the user in the active reset window. One credit equals one hour of AI Tutor course engagement
credits_remaining
The user's effective AI Tutor credit limit minus credits used, floored at 0. This is null when no effective limit is configured
percentage_credits_used
The share of the user's effective AI Tutor credit limit that has been used. 1.0 means 100%. This is null when no effective limit is configured
is_limit_exceeded
Whether the user's credits used are greater than their effective AI Tutor credit limit
last_credit_usage_at
The timestamp of the user's most recent AI Tutor course engagement event in the active reset window
ai_tutor_default_user_limit
The default per-user AI Tutor credit limit for members of the group
ai_tutor_custom_user_limit
The user's active custom AI Tutor credit limit, if one is configured
ai_tutor_effective_user_limit
The user's current AI Tutor credit limit after resolving custom, default, then group limits
ai_tutor_limit_source
The level that provides the effective user limit: custom, default, or group
ai_tutor_custom_limit_created_at
The timestamp when the active custom user limit was created
ai_tutor_group_limit
The current group-level AI Tutor credit allocation, repeated on each user row and used as the final fallback limit
Last updated