An effective data management strategy ensures that data remains accurate, secure, and scalable across its entire lifecycle. This article explores proven methods for building such a strategy — from performance optimization to automation and AI-powered analytics.

It covers:

  • Core principles of database performance, security, and integrity

  • The role of automation in backups, deployments, and change management

  • How to apply least-privilege access and role-based security policies

  • Practical steps for creating a governance framework and measurable KPIs

  • How AI can accelerate SQL coding, optimize queries, and forecast data growth

The article also highlights how dbForge Edge, a feature-rich database IDE for SQL Server, MySQL, MariaDB, PostgreSQL, Oracle, and a wide range of cloud services, helps apply these best practices through automation, schema comparison, and source control.