Insurance, pharmaceutical, CPG, construction and pension organisations use RightData to automate data quality, reconciliation and audit evidence. Every story below is a named, published customer programme.
Automating Data Quality Assurance Across 7 Insurance Brands
As they transitioned to a more agile DevOps model, they needed a solution for data quality assurance that could integrate into their CI/CD framework while supporting their complex data platforms across Accident Fund, United Heartland, CompWest, and other brands.
80% reduction in manual testing effort
Continuous data quality monitoring across 7 brands
Ensuring SOX Compliance Through Automated Data Integrity Validation
Being a publicly traded company, Granite must adhere to strict regulatory standards when it comes to financial reporting and SOX compliance. Ensuring data integrity and quality is of utmost importance and is challenging with the volume and variety of data flowing across the organization. Out of compliance has significant financial and compliance risk which can lead to major business impact.
Continuous SOX compliance monitoring
Automated data integrity validation for SEC reporting
Automating DataOps for Enterprise Analytics Platform
The team had built a custom python/robot framework for test automation, but it proved to be expensive and time consuming to develop and maintain. The output generated was overly technical and confusing for the PADL's SQA team. The framework was missing orchestration processes, resulting in the need for manual triggers.
Enterprise Data Governance Across Global Operations
Managing metadata and master data across 48 instances with a 4-tier landscape created significant complexity. Customers and vendors were experiencing delays, and the lack of synchronization between global and regional systems was impacting operational efficiency.
Automating Data Validations for Pension Fund Management
This manual, labor intensive process was directly impacting the team's productivity. An estimated 50% of the Business Analysts team's time, approximately 8 man hours per day, was going towards executing this manual process across multiple systems.