Big Data Migration & Modernization

Big data migration moves data, workloads, and applications from legacy systems to modern platforms. Modernization goes further-re-architecting solutions to take advantage of cloud-native capabilities, managed services, and modern frameworks.

Common migration scenarios include: moving from on-premises Hadoop clusters to cloud data lakes, upgrading from legacy data warehouses to platforms like Snowflake or Databricks, migrating between cloud providers, and consolidating disparate data systems into unified platforms.

The business drivers are compelling: cloud platforms typically reduce total cost of ownership by 40-60% while improving performance and scalability. Managed services reduce operational burden. Modern tools improve developer productivity. The challenge is executing migration without disrupting ongoing operations.

We have completed over 40 big data migrations, moving more than 400TB of data to modern platforms. Every migration achieved zero unplanned downtime. Our clients have realized average cost reductions of 45% post-migration.

Big data migrations are complex. They involve moving massive data volumes while maintaining ongoing operations. Workloads must be translated to new technologies. Users need to be retrained. Our structured methodology addresses each challenge systematically.

We understand both source and target technologies deeply. Whether you are migrating from on-premises Hadoop, legacy Teradata, or an older cloud platform, we know the source system intricacies. We are experts in target platforms including AWS, Azure, GCP, Databricks, and Snowflake.