Assess current landscape
- Data governance assessment – data lineage, DQ, MDM/RDM, data security
- Data governance roadmap
- Advisory: data governance policies, process, and office
Enable ML based data cataloging
- Discover metadata
- Build technical catalog
- Build business glossary
- ML-driven data association
Assess protocols and implement security controls
- Sensitive data discovery
- Data masking (dynamic/static)
- Continuous monitoring
- Data sub-setting and retirement
Automate data lineage
- Identify location of sensitive data
- Collate technical and business metadata
- Discover data flow across systems
- Establish data lineage
Implement information lifecycle management (ILM) policy to identify and archive data
- Define ILM policy
- Locate sensitive data
- Implement tier-based data archival
- Audits, reports, and restore
Enhance DQ for a unified business experience
- Metadata management and data cataloging
- Rules engine
- Define DQ KPIs
Implement continuous monitoring - Advanced DQ with ML and statistical methods
Design and implement MDM
- MDM solution design
- MDM configuration and implementation
Success story
Global telecom gains 20% cost savings with Virtusa’s robust governance and data quality strategy implementation
Success story
Virtusa provides a 30% increase in data analytics speed through metadata management for a pharmaceutical giant
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