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Tony - Database Engineer

Database engineer for query optimization, data analytics, and multi-platform database insights.

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Core Capabilities

Data Analytics

• Data pattern analysis and business insights • Performance metrics and trend analysis • Query performance analytics • Database usage and cost analytics

Database Operations

• Database monitoring and health checks • Performance tuning and optimization • Backup and recovery operations • Database maintenance and troubleshooting

Query Optimization

• SQL query analysis and performance tuning • Index optimization and design • Execution plan analysis • Query rewriting and optimization

Multi-Platform Expertise

• PostgreSQL, MySQL, MongoDB, Redis • Cloud databases: RDS, Aurora, Cloud SQL • NoSQL: DynamoDB, DocumentDB • Cross-platform data operations

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Common Use Cases

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Performance Analysis

Example: @tony analyze our PostgreSQL database for slow queries and recommend optimization strategies What you get: Query-specific optimizations with index recommendations and performance impact analysis.

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Database Configuration

Example: @tony optimize our MySQL 8.0 configuration for high-throughput OLTP workloads with 10k+ concurrent connections What you get: Tuned configuration settings with throughput improvements and resource optimization.

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Backup Strategy

Example: @tony assess our database backup strategies and design disaster recovery procedures What you get: Comprehensive backup plan with RTO/RPO optimization and automated validation.

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Migration Planning

Example: @tony create migration plan for moving our MySQL databases to PostgreSQL on AWS RDS with zero downtime What you get: Detailed migration timeline with risk assessment and rollback procedures.

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Available Tools

#dashboard

Primary Tool - Create database performance dashboards with real-time insights and analytics.

#report

Primary Tool - Generate detailed database analysis reports and data insights.

#visual

Transform database metrics into visual performance analytics.

#recommend

Get query optimization recommendations and performance improvements.

#alert

Set up alerts for database performance and capacity thresholds.

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Best Practices

Include performance context: 
✅ @tony analyze queries taking >2 seconds on our production PostgreSQL database and optimize for <500ms response time
❌ @tony make our database faster
Specify database platform: 
✅ @tony optimize our MySQL 8.0 configuration for read-heavy workloads with 10k+ concurrent connections
❌ @tony check our database
Define success metrics: 
✅ @tony design high-availability setup achieving 99.99% uptime with <1 minute failover time
❌ @tony improve our database reliability

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Configuration

Supported Platforms: PostgreSQL, MySQL, MongoDB, Redis, AWS RDS, Aurora, Azure Database, Google Cloud SQL, DynamoDB Primary Tools: #dashboard, #report (for data insights and analytics) Additional Tools: #chart, #recommend, #alert Connections: Database instances with query performance and monitoring metrics access

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Getting Started

  1. Connect your database platforms and performance monitoring tools
  2. Start with: @tony #dashboard create database performance analytics dashboard
  3. Generate insights with: @tony #report analyze query patterns and optimization opportunities
  4. Implement query optimizations and monitor performance improvements

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