success story

Virtusa Implemented a Data Warehousing Solution for a Leading eLearning Company

Our client is an innovative leader in eLearning, online training, and talent solutions for various enterprises and consumers across the globe.

The client wanted to upgrade their existing data warehouse and disparate reporting systems to make them more efficient and flexible for financial reporting.



The Challenge

Our client's existing data warehouse and disparate reporting systems were slow and cumbersome, leading to many opportunity losses. The problems included

  • Managing multiple reporting systems on different platforms and related integration issues
  • Inability of the existing data warehouse, which was developed using home-grown tools and stored procedures, to scale with growth
  • Lack of a comprehensive data model to effectively leverage the functionality of Oracle PeopleSoft EPM
  • Frequent issues related to the maintenance of the overall system
The Solution

Virtusa developed a data warehouse roadmap for efficient and flexible financial reporting and analytics. The key highlights include

  • Developed the DW architecture, leveraging Oracle PeopleSoft EPM
  • Standardized on IBM DataStage for extract, load, and transfer (ETL) and Business Objects for reporting and analytics
  • Spearheaded the DataStage ETL design, development, and performance tuning efforts
  • Designed and developed business intelligence reporting
  • Developed a migration plan to migrate to the new data warehouse
  • Designed and developed several reporting modules, including accounts receivables, royalties, and sales commissions
The Solution
The Benefit

By leading this engagement, Virtusa successfully implemented a data warehousing solution leveraging IBM Data Stage to improve operational efficiency and business agility. The key benefits include

  • Effectively leveraged our client's investments in Oracle PeopleSoft EPM
  • Improved reporting and analytics through an optimized data model and efficient data integration capabilities
  • Reduced cost by $167,000 per year by migrating data from unsupported old hardware
  • Reduced data conversion time from 40 hours to 20 hours for processing 110 million rows
  • Drastically reduced labor cost by using our global delivery model
  • Increased availability of the royalties system by 50%
  • Improved business agility with faster report generation and enhanced analytical capabilities
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