SunLife

The Challenges

SunLife required a strong, scalable data pipeline to manage increasing amounts of financial and customer data from many platforms. The goal was to upgrade the legacy data processing infrastructure while maintaining performance, cost-efficiency, and future adaptability. The key priorities were:

Automating complex ETL processes across cloud and on-premises data.
Optimizing query performance and storage efficiency.
Scaling infrastructure without adding operational burden.
Ensuring secure and accurate data transfers from Hadoop to SQL Server.

Business Impact

60% faster data queries through optimized partitioning & compression.
70% reduction in manual ETL operations via Glue automation.
99.95% ETL job reliability across 8 months.
30% improvement in reporting SLA adherence.
Improved data consistency across 3 major business units.

Our Solution

Yotta Data architected and implemented a cloud-native ETL pipeline using AWS Glue, fully integrated with SunLife’s hybrid environment.

Cloud-Native ETL

Leveraged AWS Glue to orchestrate and automate data transformations,reducing manual job management by 70%.

Data Architecture Optimization

Engineered partitioning, indexing, and compression strategies cut query times by 60% on high-volume datasets.

Hadoop Integration

Extracted structured data from Apache Hive (Hadoop) using advanced HQL queries and transferred it to a secure staging layer.

Heterogeneous Load Strategy

Transformed and mapped data into Microsoft SQL Server maintaining integrity across complex data types and business rules.

Security & Governance

Ensured end-to-end encryption, IAM-based access control,and audit logging to meet financial compliance standards.

Technologies Used

Client Feedback

“Yotta Data’s AWS-based solution brought structure, performance, and automation to a previously manual and fragmented ETL environment. Their architectural decisions helped us unlock insights faster, and at scale.”

SunLife

The Challenges

Business Impact