Conferences / SQLSaturday
Day of Data Orlando #1161
Oct 17, 2026 · Seminole State College, Sanford, FL, United States
- Conference
- SQLSaturday Database
- Dates
- Oct 17, 2026
- Venue
- Seminole State College
- Place
- Sanford, FL, United States
- Format
- In person
- Status
- Past
- Attendance
- —Sponsor text: 'Our normal attendance is in the range of 250-300', forecasting 200+ attendees (420+ registrations in 2024); capacity listed as 400. No 2026 count found.
- Website
- sqlsaturday.com
- Recorded
- 10 sponsors · 50 speaker appearances
- Notes
- Official name: Day of Data Orlando 2026. Sessions and speakers from the event's Sessionize schedule (48 sessions); affiliation taken from each speaker's Sessionize tagline where it names an organization, else null. Sponsors and tiers from the event page (logos only; names inferred from logo link/file); 'Global Sponsor' is the Microsoft + AMD co-branded logo shown on every Day of Data page. Branded 'Day of Data Orlando 2026' (page title reads 'Data of Day Orlando 2026'); Orlando's 19th annual event. 48 talk sessions in the Sessionize schedule (54 entries, of which 6 are registration, breaks, lunch and closing raffle, not counted); the paid Friday pre-con 'SQL AI App in a Day' (Microsoft) is not in the schedule. Sponsors listed without tier headings on the event page except In-Kind and Community Partner; lunch is opt-in at registration (price not stated).
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| General admission | $0 | — | Event page describes the event as free. | sqlsaturday.com |
Sponsors 10
Community 2
- DevITjobs · Community Partner
- TEKsystems · Community Partner
Speakers and talks 50
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Alvaro Costa-Neto | Amazon Web Services | — | Autonomous Database Operations using Agentic AI for SQL Server | — |
| Anishek Kamal | Microsoft | — | Three Waves, One Stack: Hadoop to Lake house to AI-Ready Data Platforms | — |
| Arunkumar Amaran | Macy's | — | From Data Chaos to AI-Ready: Building a Unified Data Foundation for the Agentic Enterprise | — |
| Avneet Bansal | — | — | Scaling Enterprise RAG with Structure-Aware Retrieval | — |
| Barkha Herman | — | — | Iceberg Ahead: Navigating the Future of Data Lakes Without Sinking | — |
| Bob Ward | Microsoft | — | Microsoft SQL and AMD in the Era of AI | — |
| Bob Ward | Microsoft | — | Azure SQL Hyperscale: The Cloud Database for the era of AI | — |
| Bradley Ball | Microsoft | — | Microsoft Fabric AI, Copilots, Data Agents, Fabric IQ, & Extending Data Agents Beyond Fabric | — |
| Brent Ozar | — | — | Watch Brent Tune a Query in SQL Server 2025 | — |
| Brent Ozar | — | — | AI in Your Career: Sidekick, Hero, or Villain? | — |
| Cecilia Brusatori | — | — | Empowering Everyone: Data Modeling in Power BI for Business Users | — |
| David Elgueta | — | — | The Friction Was Doing the Job: Redesigning Accountability for the AI-Speed Organization | — |
| David Pless | Microsoft | — | Modernizing SQL Server: Upgrade, Migrate, and Innovate with SQL Server 2025 & Azure SQL | — |
| Eddy Djaja | SQLGrease | — | Data Management in Practice: Building Trusted Data for Engineering and Analytics | — |
| Hasan Savran | SavranWeb Consulting | — | SQL Server vs. Cosmos DB: The Definitive Decision Matrix | — |
| James Serra | Microsoft | — | Deciphering Data Architectures (Modern Data Warehouse, Data Fabric, Data Lakehouse, and Data Mesh) | — |
| Jason Romans | — | — | Fabric 101: Your Park Map to Microsoft Fabric | — |
| Jayakumar Ramalingam | — | — | From Telemetry to Recovery: Building Self-Healing Cloud Systems with Multi-Agent AI | — |
| Jeevan Krishna Paruchuri | U.S. Bank | — | One Copy, Two Engines: Interoperability Between Snowflake and Databricks with Uniform | — |
| Jeff Taylor | — | — | Your Daily Driver Got an Overhaul: What's New in SSMS 21 and 22 | — |
| Jeff Taylor | — | — | How To Tune A Multi-Terabyte Database For Optimum Performance | — |
| Joanne Skiles | — | — | You Don't Need a Data Platform: Building AI-Powered Pipelines on AWS Serverless | — |
| Kevin Feasel | Catallaxy Services, LLC | — | Getting Started with DuckDB | — |
| Kevin Feasel | Catallaxy Services, LLC | — | Eyes on the Prize: Simple and Effective Dashboard Visualization Techniques | — |
| Kevin Mason | — | — | Working with Power Bi in an AI driven world. | — |
| Kevin Pereira | SHI International Corp | — | SQL in the Fabric Era: Translate existing skills into the modern data platform | — |
| Kuladeep Sandra | Dell Technologies | — | What Makes a Lakehouse AI-Ready? Building Trusted Data Platforms for the AI Era | — |
| Lav Chintapalli | — | — | Fork in the Road: Why AI Success Depends on Three Human Choices | — |
| Leonard Lobel | Sleek Technologies, Inc | — | What's New for Developers in SQL Server 2025 | — |
| Lokeshkumar Madabathula | Webilent Technology | — | From Data Engineering to Agentic AI: Building Autonomous Lakehouse Platforms | — |
| Loren Fowler | Per Scholas | — | The Human Side of AI: Why Soft Skills Matter More Than Ever Track: AI & Professional Development | — |
| Lucrecia Krause Data Platform MVP | — | — | From Data Silos to Intelligent Apps: A Microsoft Fabric Success Story | — |
| Michael Rosario | Design Interactive | — | Unlock the Power of AI Agents: Building High-Performance MCP Servers with .NET | — |
| Mike Byrd | ByrdNest Consulting | — | A HI (Human Intelligence) Technique to Manage Missing Index Hints | — |
| Nadezhda Shiroglazova | MetaLead | — | Beyond Model Accuracy: Designing a Risk-Aware LLM Agent with Confidence Gating and Human Escalation | — |
| Ratanchur Sarkar | Capital One | — | Lakehouse Architecture: Compliant, Real-Time Analytics for Regulated Industries | — |
| Rob Volk | — | — | DeepSQL: How To Discover SQL Server Internals | — |
| Ryan Conrad | Travel + Leisure | — | The Anti-Outsourcing Playbook | — |
| Saikrishna Reddy Ala | Bath & Body Works | — | Delta at Scale: Change Data Capture Patterns for SQL Server, Fabric, and the Modern Lakehouse | — |
| Sandeep Gundla | — | — | Designing Cloud-Native Applications for Performance, Scalability, and Reliability | — |
| Satyanarayana Gadiraju | — | — | Detecting the Unusual: Behavioral Analytics for Modern Data Security | — |
| Shubham Chaturvedi | — | — | Replacing a Legacy Financial Crime Platform with AWS-Native Data Pipelines | — |
| Sudhir Amin | — | — | Autonomous Database Operations using Agentic AI for SQL Server | — |
| Suryasivaji Killi | GMH Holding | — | AI Forecasting Under Uncertainty: Better Decisions for Inventory and Financial Risk | — |
| Thiru Gankidi | V-Soft Consulting Group | — | THE MYSTERY OF THE MIDNIGHT WAREHOUSE SPIKE | — |
| Tim Radney | — | — | Understanding SQL Server Backup and Restore | — |
| Tricia Diamond | Diamond PMO Solutions | — | Auditable by a Stranger: A $386 Million Federally Audited Portfolio Taught Me About Governing AI | — |
| Uchenna Egbe | Amazon Web Services | — | Tackling PII Headaches: Generating Production-Grade Synthetic Data with Agents and llms | — |
| Venu Thangalapally | Amazon Web Services | — | Tackling PII Headaches: Generating Production-Grade Synthetic Data with Agents and llms | — |
| Victor Ivantsov | — | — | My T-SQL Tricks | — |