AI-Assisted Data Platform Modernization
Seamlessly Migrate BigQuery Workloads to Snowflake on AWS
Migrating data platforms is never as simple as lift-and-shift. It’s a transformation of people, process, and architecture. For enterprises running on BigQuery, the transition to Snowflake on AWS presents significant advantages in performance, cost control, and platform interoperability. But without the right strategy, migrations can be slow, error-prone, and disruptive.
phData’s AI-Assisted Migration Services brings automation, proven methodology, and cloud-native architecture together to deliver smooth, efficient migrations from BigQuery to Snowflake on AWS. From automated SQL conversion to data validation and governance alignment, we help enterprises eliminate the risks during migration and unlock the full value of Snowflake on AWS.
Our AI-Assisted Migration Services and proprietary toolkit accelerate migrations while ensuring consistency and accuracy at every step:
- AI-accelerated migrations reduce manual effort and minimize risk
- Pre-built migration patterns and infrastructure-as-code templates
- Automated user provisioning and access management at scale
- Full migration coverage: queries, jobs, datasets, permissions, and lineage
- Post-migration support for performance tuning and optimization
How it Works
We start with a structured discovery process to assess your current BigQuery workloads, access patterns, and dependencies. Using our AI-assisted Migration Factory, we automate key steps like SQL translation, infrastructure provisioning, and data validation. Our team supports every phase from planning and execution to user enablement while aligning the migration with AWS native services for ingestion (DMS, Glue), security (Lake Formation), and orchestration (Step Functions, MWAA). The result is a clean, validated, and production-ready Snowflake environment built to scale on AWS.
Reach out to phData today to learn more about implementing a Managed Cloud Developer Environment on AWS
