Data Object Analyzer – AI-Powered Database Discovery & Diagnostics

Overview: Data Object Analyzer is an intelligent database management platform providing automated discovery, diagnostics, and performance insights across enterprise database landscapes. Data environments suffer from fragmented visibility across multiple engines, high dependency on manual SQL scripting, reactive maintenance where issues surface only after performance degrades, and tool sprawl from disconnected monitoring tools. The Data Object Analyzer addresses these gaps with a unified, intelligent interface for database discovery, profiling, health checks, and optimization — enabling teams to move from reactive firefighting to proactive management. Data Object Analyzer is part of Coforge Data CosmosTM which is our Innovation Backbone combining platforms, agentic accelerators, and services to enable end-to-end data engineering, BI, governance, and analytics.

Core Capabilities:

1. Automated DB Scanner Instant server discovery and connection validation across heterogeneous environments. Automatically detects database instances, validates connectivity, catalogs configurations, and maps topologies — eliminating manual environment setup. Supports Oracle, PostgreSQL, MySQL, SQL Server, Amazon RDS, Amazon Aurora, Amazon Redshift, and Snowflake.

2. Smart Recommendations Engine Severity-tagged advisory for query optimization. Analyzes execution plans, identifies high-latency queries, detects index inefficiencies, and provides actionable recommendations ranked by severity (Critical, High, Medium, Low) with root cause, expected impact, and suggested remediation.

3. Deep Diagnostics (6-Tab View) Comprehensive diagnostic interface with six perspectives: • Health Overview — Real-time server health, CPU/memory/disk utilization, connection pool status • Schema Analysis — Automated profiling with table structures, column types, constraints, indexes • Query Performance — Execution plan analysis, slow query identification, lock contention detection • Data Profiling — Statistical profiling of distributions, null percentages, cardinality • Dependency Mapping — Visual mapping of inter-table relationships and cross-database references • Configuration Audit — Server configuration review against best practices

4. Smart Dashboard & Unified Governance Single-pane-of-glass view across all connected databases. Tracks query latency trends, schema change history, health scores, and recommendation compliance. Enables governance oversight of database health across the enterprise.

5. Cloud-Native Deployment on AWS Deployed on Amazon EKS with integration to Amazon RDS, Amazon Aurora, Amazon Redshift, and self-managed dsatabases on EC2. Amazon Bedrock powers AI Chat (MCP). Amazon S3 stores diagnostic snapshots and audit logs. Amazon CloudWatch integration for infrastructure monitoring.

Business Benefits: • 70% reduction in environment discovery time through automated DB scanning • Proactive query optimization with severity-tagged recommendations • Democratized database insights via AI Chat — reducing Data Analyst and DBA dependency by 60% • Unified governance with consolidated Smart Dashboard across all engines • Accelerated troubleshooting with 6-tab diagnostics replacing manual SQL analysis