Data and Database Modernization

Modern data and database environments are increasingly distributed across legacy systems, cloud platforms, virtualized infrastructure, and various database technologies. Modernization is no longer a one-time migration project; it is a continuous discipline for improving database performance, data quality, scalability, reliability, governance, recoverability, and business continuity.

This book presents a vendor-neutral framework for modernizing data assets alongside database environments through four connected pillars: classification, consolidation, backup, and migration. It details data and database lifecycles, data classification, database workload classification, metadata management, consolidation architecture, backup and recovery design, archival strategies, migration planning and execution, and post-migration optimization.

By the end of this book, readers will learn how to assess legacy data and database estates, classify data and workloads, select suitable consolidation and migration strategies, design reliable backup and recovery frameworks, manage risk and downtime, validate data integrity, optimize database performance, and build modern environments that remain efficient, resilient, scalable, and ready for future change.

WHAT YOU WILL LEARN

● Assess legacy data and database environments; set modernization priorities.

● Classify data, database workloads, metadata, systems, and dependencies.

● Design resilient consolidation, backup, recovery, and continuity strategies.

● Plan and execute controlled data and database migrations confidently.

● Implement storage tiering, data aging, and metadata index retrieval.

● Optimize migrated databases for performance, cost, governance, and reliability.

WHO THIS BOOK IS FOR

This book is for database administrators, data engineers, data architects, cloud architects, system administrators, IT strategists, consultants, and upper-level computing students. Readers should possess an intermediate understanding of database systems, data modeling, infrastructure concepts, and core data management principles.