Tutor LMS keeps quiz attempts in tutor_quiz_attempts with attempt_status, earned_marks, and attempt_ended_at columns, and per-question answers in tutor_quiz_attempt_answers. Pro installs add tutor_earnings and tutor_withdraws for marketplace monetisation. The default Tutor admin gives a per-quiz review queue and buries per-question detail in the attempt screen, so cross-course chart views (pass rates, score trends, grading-queue size) all need either workarounds or custom code.

SleekView Charts reads those tables and exposes them as cards. A Number card shows the count of attempts with attempt_status = review_required across all courses. A Pie card breaks attempts down by pass, fail, and review_required share. A Bar card averages earned_marks per course or per quiz. An Area card plots attempts over time so launch effects and seasonal dips are obvious.

For marketplaces, instructor earnings join the dashboard too. A Bar card ranks instructors by total earnings; an Area card plots earnings over time. Same data the Pro reporting screens show, configurable as cards on a shared dashboard with cross-card filters that scope by course, cohort, or date range.

Tutor LMS scales across course catalogues nicely. The data model handles a five-course academy and a five-hundred-course marketplace with the same schema. What doesn't scale is the per-quiz drill-down model of the default admin.

A marketplace lead managing forty courses with rolling enrolment wants a single Number card for the cross-course grading backlog, a single Donut for catalogue-wide pass rates, and a single Area chart for attempt volume. Course designers want a per-question pass-rate Bar across the catalogue, not a per-quiz drill. Marketplace operators want earnings trends alongside academic ones on the same dashboard.

SleekView Charts treats the Tutor tables as a source for configurable cards with cross-card filters. Same data, hooks intact for any edits routed through the API, dramatically more useful as a daily marketplace dashboard.