Analytics & Reporting Service

Comprehensive analytics platform for tracking learner progress, engagement, and business intelligence

Requirements Document

Comprehensive requirements for the Analytics & Reporting Service in the KnowledgeTracker Platform.

1. Functional Requirements

1.1 Learner Analytics

  • Individual learner progress tracking across all courses
  • Time spent on learning activities and content
  • Assessment scores and performance trends
  • Skill acquisition and competency mapping
  • Learning path completion rates

1.2 Course Analytics

  • Enrollment and completion rates per course
  • Content engagement metrics (video watch time, resource downloads)
  • Drop-off points and friction analysis
  • Assessment difficulty and pass rates
  • Course ratings and feedback aggregation

1.3 Engagement Metrics

  • Daily/weekly/monthly active users (DAU/WAU/MAU)
  • Session duration and frequency
  • Feature usage statistics (forums, live classes, certificates)
  • User retention and churn analysis
  • Cohort analysis for user groups

1.4 Business Intelligence

  • Revenue analytics by course, instructor, and period
  • User acquisition and conversion funnels
  • Customer lifetime value (CLV) calculations
  • Marketing campaign ROI tracking
  • Subscription growth and churn metrics

1.5 Custom Reports & Dashboards

  • Drag-and-drop dashboard builder
  • Pre-built dashboard templates for common use cases
  • Custom report creation with filters and dimensions
  • Scheduled report delivery via email
  • Export to PDF, Excel, CSV formats

1.6 Real-Time Analytics

  • Live user activity monitoring
  • Real-time enrollment and completion tracking
  • System performance and health metrics
  • Alert triggers for anomalies or thresholds

2. Non-Functional Requirements

2.1 Performance

  • Dashboard load time < 2 seconds for standard reports
  • Real-time data refresh every 30 seconds
  • Support for analyzing 100M+ data points

2.2 Scalability

  • Data warehouse architecture for historical data
  • Columnar storage for fast aggregations
  • Data partitioning by time and organization

2.3 Data Quality

  • Data validation and cleansing pipelines
  • 99.9% data accuracy for reported metrics
  • Audit trails for data transformations

2.4 Security & Privacy

  • Role-based access control for reports and dashboards
  • Data anonymization for learner privacy
  • Multi-tenant data isolation
  • GDPR-compliant data retention policies

Requirements Validation

Use this requirements document alongside the Database Design to validate:

  • All analytics metrics can be calculated from available data
  • Event tracking schema supports required dimensions
  • Real-time and historical data pipelines are architecturally sound
  • Multi-tenant reporting isolation is properly implemented