Overview
Capabilities
Challenge
Overcoming High Incident Volumes and Lack of Structured Support in Data Operations
- Current support model struggling to maintain 24×7 stability across ETL and data platforms
- High incident volumes delaying resolution and affecting business continuity
- Limited automation leading to inefficiencies and repeat issues
- Weak knowledge management practices
Solution
AI-Driven Managed Services Model with Proactive Monitoring and Governance Framework
Coforge implemented a structured managed services approach with the following:
- Deployed dedicated 24×7 managed services model across ETL pipelines, Hadoop, Talend, Databricks, SQL, and Python platforms
- Enabled structured knowledge transfer framework for seamless transition and faster stabilization
- Implemented AI-assisted support and automation-first strategies, proactively monitoring 600+ Talend jobs
- Introduced Shift-Left practices and cognitive automation to reduce ticket volumes and accelerate resolution timelines
- Established robust service governance with real-time reporting, root cause documentation, and continuous improvement
Tools & Technology
Shell scripting, SQL, Azure Databricks, Talend, Application Monitoring tool, Python and Hadoop
Impact
Driving Operational Efficiency, Resiliency, and SLA-Based Performance Improvements
- Reduced total cost of ownership (TCO) by optimizing support operations
- Improved year-on-year productivity through automation-first delivery
- Enhanced resiliency with proactive monitoring and faster recovery
- Standardized operations with knowledge base, runbooks, and governance frameworks
- Strengthened talent quality and stability through continuous knowledge transfer
- Enabled real-time reporting for improved visibility and decision-making