Automated legacy workload migration to Snowflake
Ensure speed accuracy, and 100% preservation of business logic with LeapLogic’s automated assessment, transformation, validation, and operationalization.
Experience 4x faster Snowflake migration at half the cost with end-to-end automation in four steps
- Get answers to key questions
- Will it make sense to design my future-state architecture using all Snowflake-native services (for data processing and storage, orchestrating, analytics, BI/reporting, etc.)?
- What should be the optimum auto-scaling rule for my Snowflake cluster based on my reporting needs?
- Can I save provisioning and maintenance costs for rarely used workloads on Snowflake?
- Data warehouse
- Can I get schema optimization recommendations for partitioning, clustering, and more?
- ETL
- Will the assessment help me choose Snowflake-native services for meeting ETL SLAs?
- Analytics
- Will it be beneficial to convert analytical functions to Spark libraries or some native Snowflake functions?
- Hadoop
- Is my optimization strategy for Update/Merge apt for Snowflake?
- Can I get schema optimization recommendations for partitioning, clustering, and more?
- Packaging for and orchestration using Snowflake-native services
- Intelligent transformation engine, delivering up to 95% automation for:
- Data warehouse – Snowflake
- ETL – Snowflake
- Analytics – Snowpark on Snowflake
- Hadoop – Snowflake, Presto query engine
- All transformed data warehouse, ETL, analytics, and/or Hadoop workloads
- Business logic (with a high degree of automation)
- Cell-by-cell validation
- File-to-file validation
- Integration testing on enterprise datasets
- Assurance of data and logic consistency and parity in the new target environment
- Productionization and go-live
- Capacity planning for optimal cost-performance ratio
- Performance optimization
- Robust cutover planning
- Infrastructure as code
- Automated CI/CD
- Data warehouse – Provisioning of Snowflake and other required services for orchestration, monitoring, security, etc.
- ETL – Provisioning of Snowflake and other required services
- Analytics – Provisioning of Snowflake and other required services
- BI/Reporting – Provisioning of Snowflake
- Hadoop – Provisioning of Snowflake and other required services
Assessment
- Get answers to key questions
- Will it make sense to design my future-state architecture using all Snowflake-native services (for data processing and storage, orchestrating, analytics, BI/reporting, etc.)?
- What should be the optimum auto-scaling rule for my Snowflake cluster based on my reporting needs?
- Can I save provisioning and maintenance costs for rarely used workloads on Snowflake?
- Data warehouse
- Can I get schema optimization recommendations for partitioning, clustering, and more?
- ETL
- Will the assessment help me choose Snowflake-native services for meeting ETL SLAs?
- Analytics
- Will it be beneficial to convert analytical functions to Spark libraries or some native Snowflake functions?
- Hadoop
- Is my optimization strategy for Update/Merge apt for Snowflake?
- Can I get schema optimization recommendations for partitioning, clustering, and more?
Transformation
- Packaging for and orchestration using Snowflake-native services
- Intelligent transformation engine, delivering up to 95% automation for:
- Data warehouse – Snowflake
- ETL – Snowflake
- Analytics – Snowpark on Snowflake
- Hadoop – Snowflake, Presto query engine
Validation
- All transformed data warehouse, ETL, analytics, and/or Hadoop workloads
- Business logic (with a high degree of automation)
- Cell-by-cell validation
- File-to-file validation
- Integration testing on enterprise datasets
- Assurance of data and logic consistency and parity in the new target environment
Operationalization
- Productionization and go-live
- Capacity planning for optimal cost-performance ratio
- Performance optimization
- Robust cutover planning
- Infrastructure as code
- Automated CI/CD
- Data warehouse – Provisioning of Snowflake and other required services for orchestration, monitoring, security, etc.
- ETL – Provisioning of Snowflake and other required services
- Analytics – Provisioning of Snowflake and other required services
- BI/Reporting – Provisioning of Snowflake
- Hadoop – Provisioning of Snowflake and other required services
Trusted by Fortune 500 companies
Spotlight
Webinar
Barry Tuthill
VP - Field Operations
Sanjay Sharma
Principal Architect
Automate EDW transformation to Snowflake and leverage existing investments
Watch nowCustomer perspective
Pat McNamara
AVP, Software Development, Bath & Body Works
Chad McKibben
Director, Data Services, Victoria’s Secret
Reduced operational expenses and improved scalability by modernizing its legacy workloads
The LeapLogic advantage
4x
faster transformation
2x
lower cost
1.5x
faster validation
2x
less manual effort
Our real-world Snowflake automated migration experience
Global specialty retail company
- 80% automated transformation to an optimized Snowflake stack
- 50% time and cost saved as compared to manual migration
- 80%-85% auto-conversion of legacy Informatica and Teradata workloads to Snowflake
- 1700 Teradata BTEQ scripts transformed to Snowflake
- 50% time and cost saved as compared to manual migration
