Redshift tables: learning, courses & assessments

Structures and manages user development, supporting training, compliance and personalised learning. It defines a set of courses, activities or goals users are expected to complete as part of their training, onboarding or professional development.

Fuse uses it to: organise and assign learning paths to individuals or groups; track progress and completion of required training; support reporting and analytics for managers and administrators; and let users view, manage and complete their assigned plans.

For reporting: using_audience_enabled tells you which assignment model this plan uses — that determines which of the two assignment tables you should be counting. community_id links the plan to a learning plan community, which is the basis for the "current community members" audience metric. visibility and visibility_for govern who can see the plan at all.

Structures and manages the components of learning plans, supporting organised training, progress tracking and personalised learning. It defines each item — a course, module, assessment or activity — that users must complete as part of a plan.

Fuse uses it to: organise and sequence the steps users follow in a plan; track progress and completion of each item; let admins build, edit and manage structured learning paths; and support reporting, notifications and compliance tracking.

For reporting: counting rows per plan gives you the item count, which is the denominator behind plan progress percentages. position gives the intended sequence — join it against progress data to find the exact step where learners stall. Filter item_type before joining to content, SCORM or events.

Organises and monitors which users are assigned to learning plans, supporting training management and progress tracking. It acts as a join table linking memberships to learning plans, indicating who is expected to complete a particular set of courses or activities.

Fuse uses it to: manage and track user assignments for training, onboarding or development; display assigned plans to users and monitor progress; support reporting on plan completion; and enable notifications and reminders.

Note: this assigns via membership_id, not user_id — you need a hop through memberships to reach the person. If a user leaves the community, the membership goes and so does the assignment, which is one reason historical completion records can outlive current assignments.

Organises and monitors which groups of users are assigned to learning plans, supporting scalable training management and progress tracking. It links learning plans to audiences, indicating which users are expected to complete a particular set of courses or activities.

Fuse uses it to: assign plans to groups of users for training, onboarding or compliance; track progress and completion at audience level; support reporting for managers on group training status; and enable notifications and reminders for assigned audiences.

Note: despite the "audience" name, the exposed field list resolves to a direct user_id — no hop through memberships needed. This is the cleaner of the two assignment tables to work with. Use it where learning_plans.using_audience_enabled is set.

Monitors and reports user advancement in courses, supporting personalised learning, compliance and progress tracking. It records how far a user has advanced, including completion status, scores and other progress metrics.

Fuse uses it to: display course progress on dashboards and profile pages; support reporting and analytics for managers and administrators; trigger notifications, reminders or unlock next steps; and enable compliance tracking for mandatory training or certification.

No description was provided in the source. Added here for orientation. Defines each SCORM package uploaded into Fuse, including its asset location, launch behaviour, approval requirements and certificate settings.

For reporting: state tells you whether the package is live. certificate_enabled identifies courses that issue certificates, which is usually the set that matters for compliance reporting. The three *_approval_required flags mirror the event approval model — SCORM courses can also require sign-off before a user can start them, which explains gaps between assignment and first activity. provider distinguishes packages by their authoring source.

Records and reports user activity in SCORM courses, supporting progress tracking, compliance and detailed analytics. It records user progress, scores, completion status and other SCORM-specific data for each course attempt.

Fuse uses it to: track progress and performance for compliance and reporting; display completion status, scores and activity history; support analytics, certification and regulatory requirements; and enable troubleshooting by storing detailed SCORM interaction data.

Manages course expiry policies and completion rules, supporting compliance, certification and ongoing learning requirements. It stores the configuration for how and when courses expire, and what rules apply to completion tracking.

Fuse uses it to: determine when a course should be considered expired for a user or group; enforce retake or renewal requirements for compliance or certification; trigger notifications when a course nears expiry; and support reporting on completion and expiry status.

Monitors and reports apprentice advancement in courses, supporting personalised learning, mentorship and progress tracking throughout apprenticeship programmes. It records how far each apprentice has advanced in a specific course, including completion status and performance metrics.

Fuse uses it to: display course progress to apprentices and their mentors or managers; support reporting and analytics for apprenticeship programmes; trigger notifications, reminders or unlock next steps based on progress; and enable compliance tracking for required training or certification.

Expected data: an apprentice reference, a course reference, progress metrics such as completion percentage, status, score and last-accessed date, plus standard timestamps.

Enables Fuse to create, manage and reuse assessment formats, supporting scalable and consistent delivery. It defines the structure and configuration of an assessment — questions, settings and layout — so new assessments can be generated quickly from a template.

Fuse uses it to: let admins and content creators design reusable assessment formats; streamline creation of new assessments by copying template data; ensure consistency across the application; and support versioning and updates to assessment formats.

For reporting: pass_score is the threshold that determines pass or fail, so keep it in your model rather than hardcoding a number. max_number_of_attempts and days_for_attempts_limit constrain retakes — worth showing alongside attempt counts so a low retake rate is not misread as disengagement when it is actually a cap. assessable_id + assessable_type link the assessment to whatever it is attached to.

Records, manages and analyses the outcomes of assessments, supporting user progress tracking and organisational reporting. It tracks each user's results for a specific assessment — a quiz, test or survey.

Fuse uses it to: display assessment outcomes to users and administrators; support analytics, reporting and progress tracking; determine eligibility for certifications, next steps or rewards; and enable filtering and searching of performance across users or groups.

For reporting: this is your assessment fact table — one row per attempt, so count rows for attempts and distinct user_id for people. state carries the pass, fail or incomplete outcome that most Universal Analytics assessment metrics filter on. main_result_id identifies the primary result where an assessment produces several, so filter on it to avoid double-counting. Filter deleted_at is null.

Tracks and reports user performance on assessments efficiently, supporting analytics, progress monitoring and personalised feedback. It holds aggregated data for each user related to their assessment activity — scores, completion rates and progress metrics.

Fuse uses it to: quickly display user progress and performance in dashboards or reports; support analytics and insights for users, managers or administrators; enable filtering, ranking and tracking based on results; and optimise queries by storing pre-calculated stats.

Organises and manages groups of questions, supporting flexible assessment design and efficient content reuse. It defines a set of questions that can be presented together as part of an assessment or activity.

Fuse uses it to: organise questions into reusable sets for different assessments or activities; let admins and content creators manage groups of questions efficiently; support randomised or structured delivery in quizzes and surveys; and enable reporting on question set performance and usage.

For reporting: included and formula_number affect how a set contributes to the overall assessment score — check these before assuming every question in a template counts equally. group and add_to_group support grouped scoring, which is how competency-area breakdowns are built.

Manages and delivers interactive content, supporting assessment creation, user engagement and data collection. It defines each question that can be presented to users, including its text, type and configuration.

Fuse uses it to: build assessments, quizzes and surveys by linking questions to templates; display questions to users and collect responses; support analytics, reporting and content management; and let admins create, edit, organise and reuse questions.

For reporting: type determines how you should analyse the responses — multiple choice, scale and free text all behave differently. value is the question's weight in scoring. topic_id links questions to topics, which is what makes topic-level competency reporting possible. Filter deleted_at is null.

Shows the available answers for a specific question. Linked to questions by question_id, it contains the answer body, the value of the selected answer, timestamps, and any assets such as images attached to that question.

For reporting: correct is the flag behind every Universal Analytics correct-answer metric. Note that the metrics distinguish three states — correct, incorrect and incomplete, where an answer has been marked as neither — so do not assume "not correct" means "wrong". numerator and denominator support fractional or partial-credit scoring. Filter deleted_at is null.

Manages and displays answer options for questions, supporting interactive assessments and accurate response tracking. It defines each selectable choice for a question so users can pick from predefined options.

Fuse uses it to: present answer options for multiple-choice questions in assessments, quizzes and surveys; record which choices users select; support grading, analytics and reporting; and let admins create, edit and organise choices.

For reporting: despite the name, the exposed fields make this the per-response record — it carries assessment_result_id, score, text_answer and working_out, which is where free-text and show-your-working responses live. non_applicable flags responses deliberately marked N/A, and these must be excluded from scoring averages or you will understate performance. Filter deleted_at is null.

Tracks and analyses user selections for multiple-choice questions, supporting assessment delivery, reporting and organisational insight. It is a join table linking a user's answer (answer_id) to a specific choice (question_choice_id).

Fuse uses it to: store and retrieve user responses for multiple-choice questions; support grading, analytics and reporting on results; ensure data integrity by enforcing uniqueness of choice and answer pairs; and associate responses with companies for organisational reporting.

For reporting: this is the table that lets you build answer-distribution analysis — which specific wrong answer people pick most often for a given question. That is the most actionable assessment insight available in the model, because it points directly at the content gap or the badly worded question. Filter deleted_at is null.