AI Impacts on the DBA: SQL Server Monitoring with Datavail TechBoost
Managing SQL Server environments has become exponentially more complex.
Data engineers today oversee 300% more data than five years ago—with the same team size. Manual monitoring and reactive troubleshooting can no longer keep pace with modern demands.
This PASS Data Community Summit 2025 presentation reveals how AI-driven monitoring transforms SQL Server management from reactive firefighting to predictive operations. Learn how leading organizations reduce alert noise by 40-60%, accelerate incident resolution by 30-50%, and protect business continuity through intelligent automation. Datavail shows you how we’re empowering our data engineers with AI in production to achieve these outcomes.
What You’ll Learn
- Proven AI-powered incident management that reduces mean-time-to-resolution by up to 50%
- Root cause analysis automation that eliminates blind troubleshooting and surfaces the “why” behind every issue
- Alert noise reduction strategies that helped one logistics company suppress 80% of non-actionable alerts
- Real-world examples including how a major retailer prevented availability group failures before they caused downtime
- Compliance and optimization insights from unified dashboards that consolidate monitoring across on-premises and cloud environments
About the Presenter
Mehul Joshi is a Senior Director and Practice Leader of SQL Server Services at Datavail, bringing over 18 years of IT experience to database management challenges. He leads global teams serving enterprise clients, combining strategic thinking with deep technical expertise. Mehul specializes in helping organizations manage mission-critical SQL Server environments at scale, with proven success implementing AI-driven solutions across thousands of database instances.
Frequently Asked Questions
How does AI improve data platform monitoring compared to traditional tools?
Traditional monitoring tools generate alerts when thresholds are breached, but they don’t explain why problems occur or how to fix them. AI-driven monitoring analyzes patterns across your environment, correlates multiple data points, and automatically generates root cause explanations.
What ROI can organizations expect from AI-powered data platform monitoring?
Organizations implementing AI-driven monitoring typically see 40-60% reduction in alert noise, 30-50% faster incident resolution, and significant cost savings through infrastructure consolidation. One logistics company suppressed over 80% of non-actionable alerts, allowing their team to focus on strategic work instead of false alarms. A global retailer prevented critical availability group failures that would have caused costly downtime.
Can AI monitoring integrate with our existing ITSM platform and tools?
Yes. Modern AI monitoring solutions integrate with existing incident management platforms, creating a single pane of glass across your on-premises and cloud workloads. This means you don’t need to replace your current tools or retrain your team on new systems.
How do you prevent AI monitoring from becoming just another source of alert fatigue?
Intelligent filtering is built into AI monitoring from the ground up. The system learns which alerts require immediate action and which are noise, automatically suppressing redundant or non-actionable notifications. Rather than generating more alerts, AI monitoring dramatically reduces alert volume—in some cases by 80%—while ensuring critical issues never slip through.