Coforge's Data Cosmos Data Object Analyzer
Coforge Limited
Data Object Analyzer by Coforge is an AI-powered database discovery, diagnostics, and performance insights accelerator.
Data Object Analyzer by Coforge is an AI-powered database discovery, diagnostics, and performance insights accelerator.
Data Object Analyzer is Coforge's AI-powered database discovery, diagnostics, and performance insights technology artifact engineered for enterprise database landscapes on Azure. Part of Coforge Data Cosmos™ — the innovation backbone combining platforms, agentic accelerators, and services for end-to-end data engineering, BI, governance, and analytics — it provides a unified, intelligent interface for automated database scanning, schema profiling, health checks, and query optimization, replacing fragmented tooling and manual SQL scripting with proactive database management.
The platform delivers end-to-end database intelligence through core capabilities: • Automated DB Scanner – instant server discovery and connection validation across heterogeneous environments • Smart Recommendations Engine – severity-tagged query optimization advisory (Critical, High, Medium, Low) • Deep Diagnostics (6-Tab View) – health, schema, query performance, data profiling, dependency mapping, configuration audit • AI Chat Interface (MCP) – natural language interaction with database insights • Smart Dashboard – single-pane-of-glass governance across all connected databases
Key Benefits: reduces environment discovery time by 70%, provides proactive severity-tagged query optimization, reduces Data Analyst and DBA dependency by 60% via AI Chat, and consolidates monitoring into a unified Smart Dashboard.
Key Use Cases: • Banking – performance diagnostics across core banking, risk, and regulatory reporting databases • Insurance – schema profiling and query optimization across policy admin, claims, and billing databases • Travel & Hospitality – proactive health checks for booking and reservation databases during peak loads • Healthcare – diagnostics and dependency mapping across clinical and EMR/EHR databases
The 8-week implementation engagement covers: discovery and environment scanning, platform deployment on Azure, connection setup across database engines, diagnostics configuration, Smart Recommendations enablement, AI Chat (MCP) setup, Smart Dashboard configuration, and knowledge transfer.
Target Audience: Database Administrators (DBAs), Data Engineering & Platform Teams, Data Architects, Cloud Migration Leads, and IT Operations & Infrastructure Teams.