Objective:

The organization performs data analysis and applies predictive analytics to identify and target potential markets. Its existing on-premises data extraction, data quality and analysis platforms were not scalable, posed stability issues and were costly to support and maintain.

Solution:

Unisys Cloud solutions team deployed a hybrid cloud solution to modernize the company’s extract, transform and load (ETL) platform within an Amazon Web Services (AWS) cloud environment, including:

• Building a platform to run in an AWS cloud environment that enables ETL functions, data quality, cleansing and analysis capabilities and offers high availability and fault tolerance using native AWS services
• Migrating storage data to a fully managed AWS Oracle RDS (Relational Database Service)
• Migrating from Windows to a Linux distribution on Amazon Linux AMI

Results and benefits:

• Realized a 40% reduction in compute resources required to support volume and capacity
• Lower total cost of ownership (TCO) through reduced capital expenditure and greater agility through cloud deployment
• Minimized recovery time objective (RTO) and recovery point objective (RPO)
• Increased productivity by working more efficiently at the system level, including database cloning, data masking, data restore and rollback, profiling of sensitive data, data lineage and production and non-production database backups