Analytics Dashboard
Live KPIs and trend charts powered by aggregated SQL queries against a normalized relational database.
Total Records
48,291
↑ 14.2% vs last month
Active Queries / min
312
↑ 8.7%
Avg Response
84 ms
↓ 18.5% faster
Storage Used
2.4 GB
↑ 6.3%
Monthly Row Insertions
Table Distribution
| Query | Table | Rows | Duration | Status |
|---|---|---|---|---|
| SELECT … GROUP BY month | orders | 12,440 | 62 ms | OK |
| SELECT … WHERE status = 'active' | customers | 8,192 | 41 ms | OK |
| SELECT … JOIN products ON … | order_items | 31,880 | 218 ms | Slow |
| UPDATE … SET last_seen = NOW() | sessions | 247 | 19 ms | OK |
| DELETE … WHERE created_at < … | logs | 5,601 | 88 ms | OK |
Documentation
A breakdown of the database design, schema decisions, and query architecture behind this dashboard.
Overview
Describe what the dashboard shows, the business problem it solves, and who uses it.
Database Schema
Describe your tables, relationships, primary/foreign keys, and normalization approach.
Key Queries
Walk through the most important SQL queries powering each chart and KPI. Include any CTEs, window functions, or indexing strategies used.
Performance Considerations
Explain indexes added, query optimizations made, and how you measured/validated the improvements.
Technologies
- Database engine: e.g. MySQL 8 / PostgreSQL 15
- Visualization layer: e.g. Chart.js / Grafana