[Provide a clear and concise description of the analytics requirement, including the specific data insights or reports needed.]
[Explain the existing analytics setup, including what data is currently being collected, how it is processed, and any limitations or gaps.]
[Detail the improvements needed to enhance analytics, such as adding new data points, refining reporting methods, or integrating additional tools.]
• [Identify and outline the first actionable task for improving data analytics.]
• [Specify the second actionable task needed for implementation or testing.]
• [...continue listing all relevant tasks...]
• [Clearly define the first success condition or expected outcome after implementing analytics improvements.]
• [Specify the second success condition or expected outcome.]
• [...continue listing all acceptance criteria...]
Enhance the Matrix Operator Dashboard to provide real-time insights on system anomalies, agent movements, and user behavior within the simulation.
• Logs capture general system events, but lack detailed user activity tracking.
• Agent activity reports are delayed and lack geospatial visualization.
• Anomaly detection only flags major glitches (e.g., déjà vu events) but misses smaller distortions.
• Data is stored but not efficiently visualized, making pattern recognition difficult.
• Track and visualize real-time agent locations within the simulation.
• Add detailed user session analytics (entry points, duration, behavior).
• Improve anomaly detection algorithms to catch subtle simulation distortions.
• Integrate a dashboard with interactive data visualizations for operators.
• Implement real-time location tracking for agents.
• Enhance session analytics to track user movements & interactions.
• Refine anomaly detection with machine learning-based pattern recognition.
• Build an interactive analytics dashboard with filters & alerts.
• Conduct testing & calibration to reduce false positives in anomaly detection.
• Operators can view real-time agent locations on an interactive map.
• User session data includes entry points, time spent, and behavioral trends.
• Anomalies (even minor ones) are accurately detected & flagged.
• Dashboard provides clear, actionable insights with alerts for critical events.