
Developing Data Governance Framework
InsuranceBusiness Impacts
Data Quality Dashboard
Data Quality Rules and Remediation Plan
Data Quality Profiling Roadmap
Data Monitoring and Control Framework
Customer Key Facts
- Location : North America
- Industry : Insurance
Problem Context
The customer, a large provider of supplemental insurance offering financial protection to more than 50 million customers worldwide, wanted to increase data steward engagement, define and implement a governance process across reporting functions, and refine their MDM data quality.
Challenges
- Identify critical objects and their attributes for data quality
- Capture data quality rules with the help of data stewards
- Develop an execution plan for the data remediation process
Technologies

Informatica

SQL Server

Tableau
Solutions
Quantiphi helped to set up a Metadata Manager framework, defined and implemented Data Quality Metrics and initiated a Data Quality project with iterative delivery of remediation efforts.
Results
- Drive RSA regulatory compliance with comprehensive collection, monitoring and evaluation of business quality assurance data for higher level of consumer data protections
- Improved visibility of quality metrics to stewardship community