Implement a new aggregation pipeline in the statistics module that groups export events by month and user ID, computing total exports per user per month. The pipeline uses MongoDB's $group stage with date truncation to month granularity, and stores results in a new `monthly_export_stats` collection. This enables generation of per-user activity reports for the admin dashboard.
Implement a new statistics module that records export operations per region and month, storing aggregated counts and total volumes in a dedicated stats table. The module includes a background job that runs daily to compute and persist the statistics from the export logs, enabling future dashboard queries without real-time aggregation overhead.
- Implemented new ExportStats model with fields for total exports, successful exports, and failure counts
- Added monthly aggregation logic to compute export metrics from the exports table
- Updated admin dashboard controller to fetch and display export statistics for the current month
- Created new API endpoint `/api/admin/export-stats` returning JSON with export counts and success rate
- Added frontend component to render export statistics as a summary card on the admin dashboard
Implement a new monthly export statistics feature that records and aggregates export operations by month, including total exports, successful exports, and failure counts. The change adds a new `export_statistics` table with columns for month, year, total_exports, successful_exports, and failed_exports, along with a stored procedure to increment counters atomically. The analytics dashboard now displays a monthly export performance chart using this data.
Implement new aggregation logic in the export statistics module to compute monthly totals grouped by region, replacing the previous flat summary. The change introduces a `compute_monthly_stats` function that processes raw export records and returns a structured dictionary with per-region counts and revenue.
