Organizations today face increasing pressure to modernize data platforms, accelerate cloud adoption and unlock AI-driven innovation. Yet large-scale migrations remain one of the most complex, time-consuming and risky initiatives enterprises undertake. Teams must assess thousands of objects, modernize legacy code, migrate critical data, validate outcomes and maintain business continuity throughout the process.
To solve these challenges, enterprises typically pursue one of two paths. Some organizations choose to modernize their workloads, transforming legacy databases, applications, pipelines and analytics environments into Snowflake-native architectures optimized for long-term innovation. For highly complex Teradata migrations, Snowflake has introduced a virtualization-based approach that enables organizations to rapidly unlock value from AI and analytics across their Teradata estate while reducing migration risk and avoiding extensive rewrites, downtime or business disruption. This approach also helps organizations accelerate time to value and reduce the risk of missing critical Teradata renewal milestones. In practice, many organizations leverage both approaches as part of a phased modernization strategy.
