LearnDash Reports by Wisdm produces tabular reports against the LearnDash data: enrolment by user, completion by course, quiz scores per attempt, time spent per lesson. The information is correct, but it is a list. A two thousand row table of completion records answers a question only if the operator already knows which question to ask, and a programme review usually starts further back than that.

The raw signal lives in learndash_user_activity (one row per enrolment, completion, lesson access, quiz attempt) and learndash_user_activity_meta (the percentage scored, the time elapsed, the attempt outcome). Those two tables are the source of truth for every report Wisdm renders. SleekView Charts reads them too, with the same access patterns the LMS itself uses, so a chart card never disagrees with the underlying report.

The difference is the surface. Where Wisdm gives a CSV, SleekView gives four chart cards on one screen: enrolments this month as a Number, course mix as a Pie, top courses by completions as a Bar, enrolment trend as an Area. The questions a programme owner asks in a quarterly review ("is the catalogue growing or shrinking", "which courses do the work") are visible in three seconds rather than after a fifteen-minute Excel session.

Wisdm Reports produces the data a programme owner needs, but it produces it as tables. Tables answer specific questions that the operator already knows to ask, and most programme reviews start more open ended than that. A dashboard answers the questions you forgot to ask: a course that quietly drove half the enrolments last month, a completion rate that started sliding three weeks ago, a quiz whose average score dropped after a content refresh.

Putting the same learndash_user_activity rows on a Number, Pie, Bar and Area card collapses a fifteen-minute Excel session into a three-second glance. The numbers do not change. The time to see them does.

A monthly programme review takes the same data and turns it into a meeting that ends with decisions rather than with a request for more data. That is the operational shift, with no separate analytics store and no scheduled aggregation job.