Data Cosmos Data Quality Framework – AI-Driven Continuous DQ Management
Coforge Limited · Cybersecurity & IT
Certification per AWS Marketplace.
Evidence tier Source Confirmed · 3 captures on record
What the publisher says
As described on AWS Marketplace.
Overview:
Coforge Data Quality Framework is an AI-driven continuous DQ management framework ensuring accuracy, completeness, consistency, and timeliness. Poor DQ costs millions in rework and compliance failures. This framework provides structured profiling, cleansing, improving, and monitoring at scale — powered by Agentic DQ Resolver. Part of Coforge Data Cosmos™ – the innovation backbone comprising platforms, agents, and services that accelerates execution across every phase of the data lifecycle.
Show the rest of the publisher’s description (41 more lines)
4-Phase DQ Lifecycle:
Phase 1: ASSESS
- Information Needs & Gaps — Assess current DQ state against business requirements
- Data Profiling — Automated profiling of distributions, completeness, validity, uniqueness
- Baseline DQ metrics and identify critical data elements requiring governance
Phase 2: PLAN
- Define DQ vision, objectives, and priorities through the Business Case & Change Council
- Design DQ rules, thresholds, governance policies; assign stewardship and accountability
- Plan cleansing strategy: correction rules, standardization logic, deduplication approach
- Establish scorecard KPIs and reporting cadence for executive and operational visibility
Phase 3: INNOVATE
- Deploy Agentic DQ Resolver — AI-based technology artifact for autonomous anomaly detection, intelligent DQ fix recommendations and subsequent remediation of quality issues
- Introduce ML-based entity resolution for fuzzy matching and duplicate consolidation
- Enable AI-driven continuous monitoring with predictive alerting on degradation
Phase 4: EXECUTE
- Apply automated correction, cleansing, standardization, and enrichment across production data
- Activate centralized rules engine — DQ rules enforced consistently across all pipelines
- Deploy DQ dashboards, scorecards, and BI reporting for real-time visibility
- Monitor continuously with AI/ML-driven alerting; update logic to prevent recurring issues
- Manage DQ knowledge base — best practices, playbooks, trend analysis
Governance Layer:
- Business Needs — Vision, objectives, pain points
- Governance — Policies, Stewardship, Standards
- Business Case & Change Council
DQ Value-Added Services:
- BI Reporting — Dashboards and scorecards
- Analytics — Trend analysis, root cause, predictive insights
- Enrichment — Data augmentation
- Workflow — Automated issue routing
Industry Applications:
- Banking — DQ profiling for BCBS 239. Continuous monitoring for regulatory accuracy.
- Insurance — Claims DQ with deduplication. DQ scorecards for actuarial teams.
- Travel — Booking DQ across GDS feeds with format standardization.
- Healthcare — Patient DQ with PII/PHI profiling and HIPAA compliance.
Business Benefits:
- Automated 4-phase lifecycle reducing manual effort by 40–60%
- Continuous AI/ML monitoring with proactive alerting
- Centralized rules engine for consistent DQ
- DQ scorecards for executive visibility
Cloud-Native on AWS:
Deployed on Amazon EKS. Amazon Bedrock for AI. AWS Glue for profiling. Amazon S3 for reports. CloudWatch for alerting.
Highlights
Highlighted by the publisher on AWS Marketplace.
Proven 4-phase lifecycle: Assess → Plan → Innovate → Execute with continuous monitoring
Powered by Agentic DQ Resolver — AI-based technology artifact for anomaly detection and validation
Centralized rules engine and DQ scorecards for executive and operational visibility
Agent build and provenance
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Compliance
- FedRAMPConfirmedNot listed90%, registry-checkedNo FedRAMP Marketplace entry matched this vendor's domain, checked 2026-08-27registry recordas observed 2026-08-27
Confirmed means matched to a public authoritative registry. Claimed means the vendor or its listing states it, not yet cross-checked. A framework not shown was not found in any source we hold, which is not evidence against it. Not listed means a scoped registry check found no match for this vendor's domain: a No is a scoped registry check, not a compliance judgment. Confidence bands: 95% domain-verified, 90% registry-checked, 80% self-attested, 70% weak signal. Self-attested items marked “vendor's site” are gathered from the vendor's own website and are not verified by us.
Vendor
External enrichment · as of 2026-08-29
Sources
Linked repositories
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