Modernizing data architecture for operational efficiency, agility, and scalability

An American insurance giant modernized their data architecture with Systech’s migration solution, resulting in enhanced data processing efficiency, improved scalability, and a 34% reduction in data load times. 

BUSINESS NEED

The client, a leader in the insurance services sector, faced challenges with their legacy systems owing to the volume of customer data. To improve operational efficiency, minimize technical debt, and future-proof their data infrastructure, the client sought a comprehensive modernization solution to address their evolving needs.

SYSTECH’S DELIVERY

A streamlined MDM refactor strategy, migrating the client’s existing data architecture to Snowflake and DBT. This shift enabled improved data lineage visibility, performance enhancements, and automation across various data processing workflows.

OVERVIEW

The monolithic architecture of IICS and Redshift lacked the flexibility and scalability needed to handle the data volumes, resulting in prolonged processing times, technical debt, and intricate code structures. By refactoring their platform with DBT and Snowflake, Systech’s solution transformed the data pipeline to improve performance and scalability while minimizing disruption to business operations.

THE CHALLENGE

The client experienced several operational challenges, including inconsistent data loads that caused frequent delays and unpredictability. The legacy systems had accumulated significant technical debt, with complex code that limited efficiency and visibility into processes. Additionally, fragmented data across systems resulted in poor data lineage, making troubleshooting and data tracking inefficient. Furthermore, the client’s reliance on IICS and Redshift created a strong vendor lock-in, making it difficult to transition to modern systems without requiring a major overhaul of their existing architecture.

THE DETAILED SOLUTION PROCESS

To revamp the current system and to address the operational shortcomings, Systech introduced a scalable solution, leveraging DBT and Snowflake to deliver enhanced speed, performance, and efficiency.

Breaking down complex IICS jobs into smaller, manageable DBT models was the first step in the migration process. This refactoring simplified data processing, making it easier to trace data lineage, and allowed for better management of data transformations.

Leveraging DBT’s simplified models and Snowflake’s scalable infrastructure improved overall data processing time by 60%, significantly boosting pre-MDM and post-MDM batch performance.

Continuous integration and delivery (CI/CD) pipelines were set up using Git for version control and Flyway for Snowflake. This enabled rapid and automated deployments, leading to more efficient development cycles and faster production rollouts.

Advanced data governance implementations, with end-to-end lineage tracking, added to Snowflake’s data masking policies safeguarded the sensitive data, ensuring full compliance with regulatory standards and improving overall data security. This provided the client with a modernized data infrastructure that significantly enhanced their performance, governance, and scalability.

THE IMPACT

Dropping from 255 minutes to 103 minutes, the solution resulted in a substantial reduction in data load times. This 60% performance boost increased operational efficiency, allowing the client to process data faster and meet business demands more effectively.

Improved governance and automated quality checks ensured that data was accurate and reliable. This led to fewer errors, more consistent data, and a stronger foundation for data-driven decision-making.

The cloud-native architecture of Snowflake provided the flexibility to scale seamlessly as the client’s data volumes grew. This enabled efficient handling of increasing data sizes and more complex queries without sacrificing performance.

Refactoring the legacy system into smaller, modular DBT models reduced the overall complexity of the data infrastructure. This made the system easier to maintain, troubleshoot, and upgrade, providing better visibility into data processing and reducing the accumulation of technical debt over time.

By boosting performance, increasing scalability, and improving data quality, Systech’s solution reduced technical debt and provided the flexibility needed for future growth, laying the foundation for long-term scalability, better governance, and more reliable data operations.

THE ADDED VALUE

The DBT models and Snowflake’s cloud platform minimized disruptions and enabled seamless scalability and data integration. By delivering a future-ready, scalable architecture that optimized data processing, governance, and efficiency, Systech positioned the client for long-term success with a modern, efficient data infrastructure.

Curious how Systech’s Snowflake solutions can benefit your business? Learn more today! https://systechusa.com/snowflake  

Maximize your data potential with Systech’s proven data management strategies. https://systechusa.com/data-management/  

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