Legacy Hadoop to Cloud Modernization

Challenge – High Costs and Slow Data Processing
A global financial institution relied on aging on premises Hadoop clusters to manage over 10PB of transaction data. High maintenance costs, slow batch jobs, and limited scalability delayed fraud detection and compliance reporting.

Solution – Cloud Migration and Data Pipeline Modernization
NucleusTeq migrated legacy HDFS workloads to AWS S3, refactored MapReduce jobs into optimized Spark applications running on EMR, and automated ETL pipelines for seamless data movement. Schema refactoring and performance tuning improved compatibility with analytics and fraud monitoring tools.

Impact – Faster Analytics and Cost Optimization
• 35% reduction in infrastructure costs
• 45% acceleration in data processing speed
• Real time fraud analytics enabled for 5M+ daily transactions

With a modern cloud native foundation, the institution achieved agility, efficiency, and faster regulatory responsiveness at scale.