1. Dataset Name

tm_learnings_v2

2. Description

Employee-level learning and development activity dataset that unions three sources of skill-building activity — completed courses, completed internal projects, and upskilling plan progress — each denormalized to one row per activity-skill combination, enriched with employee attributes.

3. Source Tables

• customer_views.course_attendance
• customer_views.courses
• customer_views.project_teammembers_details
• customer_views.profile_upskilling
• customer_views.employee (joined twice — appears to be a redundant duplicate join rather than intentional double enrichment)

4. Grain

One row per (profile_id, skill_name, activity record), where "activity record" is one of: a completed course (one row per skill tagged to that course), a completed project (one row per project teammate record), or an upskilling plan update (one row per skill tagged to that plan).

5. Dashboards Supported

• Learning & Development / Course Completion Dashboard
• Skill Building / Upskilling Dashboard
• Project-Based Learning Dashboard

6. Metrics Supported

7. Known Exclusions / Filters Applied

• Course rows included only where completion_date is not null — in-progress courses excluded.
• Project rows included only where project_completed_ts is not null — in-progress projects excluded.
• Upskilling rows have no equivalent completion-status filter — check completion_percentage for actual progress, not the presence of a completion date.
• completion_percentage is hardcoded to 1 (100%) for Course and Project rows, regardless of partial completion — consistent with the filter above, but this field can't distinguish partial completion for those two source types.
• Many columns are source_type-conditional — populated for one source type and null for the others. Always filter/group by source_type before interpreting these columns.
• Employee is joined twice on the same key, which appears to be a redundant/duplicated join rather than an intentional enrichment — flagged for cleanup, though it shouldn't inflate row counts since profile_id is unique.

8. Schema