Generative AI - Database Footprint Reduction - ServiceNow

Business Dilemma / Challenge:

The foremost IT enterprise encountered considerable hurdles in effectively handling and processing extensive database storage, grappling with instance performance issues, and enduring prolonged durations for upgrades and cloning processes.

A successful implementation of Generative AI for reducing the database footprint in ServiceNow not only optimizes the system's performance and efficiency but also contributes to cost savings and improved resource utilization.

Approach & Solution / Remedy Method:

• Data Deduplication: Build Generative AI algorithms that? can identify and merge duplicate or redundant records within the ServiceNow database
• Data Compression and Optimization: Configure AI algorithms that? can analyze data patterns and usage to optimize storage by compressing less frequently accessed data or by using more efficient storage methods without sacrificing accessibility
• Automated Data Archiving: Intelligently identify historical or less frequently used data and automatically archive it, moving it to long-term storage
• Predictive Data Pruning: By analyzing usage patterns and relevance, Generative AI can predictively prune or remove unnecessary data

Business Outcomes:

• Reduction in Storage Utilization: 40% Database size reduction.? Measure the decrease in storage consumption after implementing Generative AI-driven optimization techniques
• Improved Performance: Evaluate the improvement in query response times and overall system performance.?
• Simplified Maintenance: 15 to 20 hours reduction on Instance Clone and upgrade time ( for >10 TB Database)
• Cost Savings: Quantify the cost savings achieved through reduced storage requirements and streamlined database management.

ServiceNow Capabilities / Tech Stack Recommendations

• AWS S3 Bucket / Microsoft SharePoint
• Generative AI
• Now Assist
• Service Portal
• Azure OpenAI Collector