Case study – Retail

Fortune 100 Retailer

Use Case: Designing and implementing new database maintenance process to reduce cost, improve efficiency and availability, and enhance customer satisfaction

A Fortune 100 major retailer that operates a multibillion-dollar business, serving millions of customers across the country.

The Client’s Enterprise Infrastructure Management (EIM) team was tasked with supporting and maintaining extremely large warehouse databases in addition to other duties such as supporting human resources applications and storing business intelligence.
With continuous growth in the number of database objects, users and concurrent database access-requests, the workload was growing faster than the Client could manage. Outages and query performance degradation were starting to creep into the system. The Client’s manual methods of database monitoring and maintaining were ill-equipped to meet SLAs and leadership was vocally concerned about performance and availability.

The Client turned to Yash Solutions to develop and automate a process for continuous and proactive database health monitoring that would include health checks and a threshold alert mechanism for optimum performance and improved availability. Yash’s extensive experience writing new database monitoring and maintenance scripts and modifying existing ones made them a natural choice for the job.
Along with designing and implementing the new process, Yash improved re-orgs and run-stats with new options and better database backup performance. They also added new methods for tracking database-resource usage thresholds, new troubleshooting techniques, and better database configuration and object design so as to achieve scalability and improve performance.
The solution was not only cost-effective and provided proper documentation but it also saved over 10 terabytes of disk space and improved performance by reducing I-O cost.

The solution Yash implemented cut down the database total cycle time for ETL operations. It also improved query performance for end-user reporting needs. Additionally, an automated database maintenance process and a timely alert system cut down downtime even more. Thanks to compression, space was used more intelligently among different subject areas. Yash provided well-documented instructions to provide step-by-step guidance for on-call support or troubleshooting.
Specific gains included: Improved ETL performance that reduced cycle time by five hours
Reduced totalused-disk space by 10.5 TB
Reduced database backup time by three hours
Automated database monitoring
Health checks
Monitored time reduced by seven hours
An average saving of query performance of 1.25 hours
A 100% satisfied SLA report for the last three months
Unplanned outages reduced from an average 12 hours a month to two