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Explore the transformation potential in your business
/ Assessment
- Get answers to key questions
- Will it make sense to design my future-state architecture using all Snowflake-native services (AWS/Azure/Google Cloud) for data processing and storage, orchestrating, analytics, etc.?
- What should be the optimum auto-scaling rule for my Snowflake cluster based on my reporting needs?
- Data warehouse
- Can I get schema optimization recommendations for partitioning, clustering, etc.?
- ETL
- Will my ETL processing SLAs impact my choice for an optimum Snowflake cluster size?
- Hadoop
- Is my optimization strategy for Update/Merge apt for Snowflake?
/ transformation
- Packaging and orchestration using Snowflake-native services
- Intelligent transformation engine, delivering up to 95% automation for:
- Data warehouse to Snowflake migration –Snowflake
- ETL to Snowflake migration – Snowflake
- Analytics to Snowflake migration – Snowpark on Snowflake
- Hadoop to Snowflake – 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
- Provisioning of Snowflake and other required services
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Explore resources to support your transformation initiatives
CASE STUDY
Hadoop modernization to Snowflake enabled a single source of truth
WHITE PAPER
Automated transformation of ETL, data warehouse, and analytics to Snowflake
Webinar
Automate data warehouse to Snowflake migration
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