Case Study

Scaling Smarter Through AWS and Snowflake Data Migration

challenge

Slow Data Processing Hindering Innovation

Our client was facing some serious scalability roadblocks due to their outdated database infrastructure. This supply chain SaaS company’s existing on-prem SQL Server-based data warehouses lacked the capacity to support new customers and products, and adding hardware wasn’t an option for them. Additionally, lengthy ETL processing times (up to 48 hours on weekends) hindered their ability to be truly agile. They needed a partner with deep experience in data migration to help them scale and transform their performance.

Key Outcomes
98%
faster processing

Weekend ETL jobs slashed from 48 hours to ~1 hour

50%
faster nightly processing

Reduced batch processing times by half

solution

Cloud-First Transformation

To help future-proof their business, we designed and implemented a scalable, Cloud-first data strategy leveraging AWS and Snowflake, which included:

  • Cloud Migration & Modernization
    • Lift-and-shift migration of three data marts (AIMS Prod, IPC, Sysco) into Snowflake
    • Configured Snowflake configuration on AWS for optimal performance and scalability
    • Established a BI Mart in AWS, enhancing accessibility and efficiency
  • Optimized Data Processing & Performance
    • Converted 30+ SQL stored procedures into Snowflake JavaScript Stored Procedures
    • Enabled real-time data updates (throughout the day vs. nightly batch updates)
    • Leveraged Change Data Capture (CDC) with Fivetran for seamless data replication
    • Implemented CI/CD pipelines with Octopus and Redgate Flyway for continuous integration
  • Seamless Business Intelligence & Reporting
    • Reconfigured MicroStrategy to work with both Snowflake and legacy SQL BI Mart
    • Optimized queries and reporting workflows for faster insights
    • Implemented Airflow for automation, logging, and alerting

results

A Future-Ready Data Ecosystem

Our AWS and Snowflake-powered solution dramatically transformed data operations, improving performance and cutting costs. This led to:

  • 98% Faster Processing: Weekend ETL jobs slashed from 48 hours to ~1 hour
  • 50% Faster Nightly Processing: Reduced batch processing times by half
  • Cost Savings: Eliminated on-prem SQL servers, cutting hardware & maintenance costs
  • Scalable Storage and Compute: Snowflake’s pay-as-you-go model reduced costs by optimizing disk space and compute power

By modernizing its data infrastructure with AWS & Snowflake, our client eliminated bottlenecks, unlocked real-time insights, and positioned itself for scalable growth.

Want to learn more? Let’s talk.

tech used

AWS, Snowflake
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