Prepare Your Data Estate for AI: A Practical Path from Legacy SQL Server to the Cloud
Webinar Speaker: Donald Farmer, Research Fellow
Date: Thursday, August 20, 2026
Time: 9:00 a.m. PT / 12:00 p.m. ET
AI adoption is accelerating, and every AI initiative performs only as well as the data that supplies it. Agents, analytics, and automated operations all need data that is unified, governed, secure, and fast to query; AI readiness therefore begins with the databases an organization already runs.
Yet in many organizations those databases remain on aging SQL Server platforms, with workloads spread across systems, dependencies no one has fully mapped, and versions past end of support. Support for SQL Server 2016 ended in July 2026; SQL Server 2014 reached that point in 2024. Every month on an unsupported platform adds security, compliance, and operational risk and delays the work that AI depends on.
Modernization is therefore not a maintenance chore; it is the first stage of an AI strategy. Success depends on treating the estate as a whole: measuring exposure, mapping application dependencies, classifying workloads by risk and value, and sequencing a staged migration that improves security, governance, and performance at each step.
In this session, TDWI Research Fellow Donald Farmer and experts from IBM, Microsoft, and AMD draw on real-world migrations to show how organizations move legacy SQL Server workloads to Azure with limited disruption and connect those moves to wider plans for analytics, automation, and AI.
Attendees will learn:
- Why AI initiatives depend on databases that are secure, governed, and fast to query
- What staying on end-of-support platforms costs in security, compliance, and AI readiness
- How to assess an estate: locate exposure, map dependencies, and rank workloads by risk and value
- How a staged migration limits disruption while preserving options for advanced analytics and AI services
- Why infrastructure choices affect virtual machine efficiency, licensing cost, and long-term AI capacity