Snowflake Data Warehouse Transformation for a Leading Retail Enterprise

About Client

A retail company operating worldwide depended on an old data warehouse to handle its data related to sales, inventory, and customers. This posed a challenge when the business started to grow. The client’s system couldn’t keep up, causing slow performance and higher maintenance expenses. They approached Aegis for an advanced data warehouse solution.

Problem Statement

The client faced significant challenges with its legacy data warehouse, stating:

Our current system cannot keep up with our business growth. It’s expensive to maintain and fails during peak demand.

The system lacked dynamic scalability, resulting in slow query performance during peak business hours.
Server upgrades, storage expansion, and database administration required substantial investments.
Integrating data from multiple sources was complicated and time-consuming.
The infrastructure did not support modern analytics tools, restricting insights and decision-making.
Frequent system downtimes disrupted business operations and reporting.

Solutions Offered

The Aegis team migrated the client’s business Datawarehouse to Snowflake and has implemented a cloud-native solution.

Used Snowflake’s auto-scaling capabilities to handle workload demands dynamically.
Ensured cost-effective storage and high-speed analytics performance.
Simplified access and integration across business units and external partners.
Empowered advanced tools for quick insights and AI/ML model deployment.
Implemented role-based access control, encryption, and data masking for maintaining regulatory compliance.

Tools And Technology Stack Used

Cloud Platform: Snowflake

ETL Framework: Talend, Informatica

Monitoring Tools: Snowflake Performance Dashboard, ELK Stack

Security: Role-Based Access Control (RBAC), Data Encryption, Data Masking

Integration Frameworks: APIs, Snowflake Data Sharing

Development Process

Audited the existing data warehouse and identified key datasets, dependencies, and bottlenecks.
Designed a cloud-native architecture tailored to Snowflake’s strengths.
Re-engineered data pipelines for efficient extraction, transformation, and loading.
Adopted a phased approach, starting with non-critical workloads before moving core datasets.
Conducted rigorous performance tests on queries, dashboards, and reports.
Delivered comprehensive training and documentation for the client’s data teams.

Outcomes

The migration to Snowflake delivered measurable results:

Generation of Business-critical reports in 15 minutes for faster decisions compared to that previously took 2-3 hours.
40-50% reduction in operating costs due to reduced need for on-premises hardware.
The platform now supports seamless scaling during peak sales periods.
Reduced manual effort by 60% due to streamlined data integration from multiple sources.
Deployment of Advanced analytics and AI models is effective, resulting in better sales forecasts and inventory management.
90% reduction in Downtime incidents.

Conclusion

Aegis SoftTech has migrated the client data warehouse to Snowflake understanding their pain points. The client modernized their data infrastructure, and improved scalability, performance, and cost efficiency using snowflake capabilities. Their teams now access high-quality data instantly, driving faster decisions and business growth.