Success Story

• A digital manufacturing platform delivering custom parts on demand to help companies accelerate new product introductions
• Has 250+ global manufacturing partners and has manufactured 12M+ parts since 2013
• Caters to the Silicon Valley innovators besides the healthcare, automotive, aerospace, and consumer electronics industries

• Replace Redshift and other complex data warehousing systems with an easily maintainable and cost-effective solution
• Improve existing query performance and overcome existing challenges of scaling
• Apply modern-day architecture and design principles for decoupling existing front-end and backend ERP systems
• Build a next-gen analytics GUI solution for better flexibility and maintainability to save enterprise license cost
• Save the additional incurring cost to maintain nodes because Redshift does not separate storage and compute

Cybage visioned, architected, and designed a data warehouse that resulted in consolidation, cost savings, and scalability for future needs:

• Adopted Snowflake data warehousing solution for:
• NFR fulfillment, auto-scalability, better alertness, and monitoring
• Effective processed data management with different virtual warehouses and auto scaling on need basis
• Supporting semi-structured database
• Saving costs through Snowpipe delivery mechanism
• Accurate monitoring of each warehouse data and queries through Snowflake Console
• Used Fivetran as ETL for:
• Moving away from Lambda and used a more robust way to ETL while avoiding data breakage at the time of source system change
• Staging all data from respective data sources—S3, EC2, API, third-party app—to Snowflake
• Monitoring via AWS CloudWatch
• Implemented Sigma reporting with connectors for each Snowflake Analytics Warehouse on user privilege basis
• Deployed Apache Airflow as a data pipeline to decouple the systems
• Built a system that ensures scalability, effortless maintenance, and improved analytics performance

• ~40% cost savings owing to migration from Redshift and other systems to Snowflake
• ~60% improved reporting time and 0 timeouts due to optimized queries implementation
• Continuous monitoring through AWS CloudWatch
• Lowered licensing and other costs with effective Sigma implementation and fewer data syncs