Call for Speakers

Raleigh Day of Data 2026

in 3 months

Raleigh Day of Data 2026

event date

23 May 2026

location

Duke Health, 14 Moore Dr Durham, North Carolina, United States

website

dayofdata.org/2026-05-23-dayofdata1143/

Speak at Raleigh Day of Data 2026!

May 23rd, 2026

We are looking for speakers for 1-hour sessions on Saturday. The speaker call is open until March 3rd.

Please also indicate if you would be willing to present multiple sessions.

open, 14 days left
Call for Speakers
Call opens at 12:00 AM

01 Jan 2026

Call closes at 11:59 PM

03 Mar 2026

Add to calendar
Call closes in Eastern Standard Time (UTC-05:00) timezone.
Closing time in your timezone () is .

Hello Speakers,

This is an in-person event; you must be here in person to present the session.

Code of Conduct: https://dayofdata.org/coc/

Please submit your session(s) only if you are available and willing to come in person and present the session in Durham, NC, on Saturday, May 23, 2026, and agree to the code of conduct mentioned in the above link.

Regular sessions can be 60 minutes in total, including delivery and demos (if any).

Please include the session title, a complete description of the session, the level, the target audience, the speaker name(s), and the speaker bio(s).

If you have any questions, please get in touch with us at the speaker support email.

Thank you,

Raleigh Day of Data Team

all submitted sessions

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102 submissions
Submitted sessions
Leslie Welch
  • The Architecture of Trust: Building AI Projects That Deliver ROI
Courtney Woolum
  • Reworking Indexes to Support an Evolving Application
  • Modern Integration, Classic Toolset: A Practical Look at SSIS
Mala Mahadevan
  • Demystifying vector search in SQL 2025
Harsh Ranjan
  • Engineering Beyond the "Rule of Eight"
Alan Ferrandiz
  • Exploratory and Explanatory Data Analysis: from raw data to data-driven business decisions
  • The Self-Documenting Fabric: Automating Metadata with OpenAI and Microsoft Fabric
  • Beyond the Chatbox: Why Your Enterprise Needs Vertex AI Studio, Not Just an LLM
Anannya Roy Chowdhury
  • Moving Agentic Apps from Prototype to Production Responsibly
Sohil Sri Mani Yeshwanth Grandhi
  • Building Observable ML Platforms with Open Source: Lessons from FPGA Deployment
Chetan Nandikanti, Alvaro Costa-Neto
  • Cost-Optimizing SQL Server on AWS: EC2, RDS, and RDS Custom Strategies
Srilakshmi Baradwaj
  • When Good Systems Break: Designing Data Infrastructure That Actually Scales
Cameron Leblanc
  • The 3 C’s Behind Hallucination-Free Enterprise AI
show all submissions
Jason Miles
  • Data Products, Data Mesh, and Microsoft Fabric
Michael Wall
  • SQL MI - Making the leap
  • Immutable SQL Server - Pets vs Cows
  • Becoming a Master by Giving it all Away
  • Azure Storage: You want to put what where?
  • Azure Backup - ready for prime time?
Chuchu Wu
  • Can Large Language Model Agents Simulate Human Trust Behavior?
Emma Keenan
  • Motivation Management
Deep Patel
  • Decision Intelligence in Financial Services: Turning Data into Action, Not Reports
  • Real-Time Personalization in Finance: Architecture, Tradeoffs, and Risk
  • Analytics in the Age of LLMs: How AI Is Changing Metrics, Dashboards, and Decision-Making
  • Proving AI ROI in the Enterprise: Metrics That Survive the Boardroom
  • Proving AI ROI in the Enterprise: Metrics That Survive the Boardroom
Mark Wilkinson
  • Fast Backup and Restore without Touching Your Storage
Supraja Chinthala
  • AI Without the Hype: How Organizations Actually Succeed with Data & AI
Louis Davidson
  • Sharing is Caring and Writing is Sharing
  • SQL Techniques You Should Know
  • BI versus Relational Design
Ray Kim
  • So you want to be a presentation speaker?
  • Tech Writing for Techies: A Primer
  • SQL101 -- Learning about SQL: Building a Sandbox Using the Free Developer Edition
  • I lost my job! Now what?!? A survival guide for the unemployed
  • Networking 101: Building professional relationships
Peter Shore
  • Data Data Everywhere: A Look At Data Hoarding
  • Wait Wait Do Tell Me: A Look At SQL Server Wait Stats
  • Infrastructure for Data Professionals: An Introduction
  • SQL Triage: Where to Start When the Proverbial Excrement Hits the Rotating Oscillator
Arunkumar Amaran
  • Augmented Analytics for Retail Decision Support: Human-in-the-Loop Data Science
  • Conversational AI Interfaces for Retail Data Engineering and Business Intelligence
  • Foundation Models for End-to-End Retail Analytics: From Demand Forecasting to Personalized Pricing
Marilina Trevisan
  • Garbage in, hallucinations out: designing data for GenAI agents
Anusha Kovi
  • Governance-Aware Data Products on AWS: Trust Signals People Actually Use
  • Cost & Reliability Engineering for AI Analytics on AWS: Context Budgets + Query Budgets + SLAs
  • Permission-Aware RAG for Analytics on AWS: Prevent “Smart Data Leaks”
  • Incident-Grade Lineage on AWS: Run-Level Evidence That Cuts MTTR
  • Trustworthy Conversational BI on AWS: Bedrock + Semantic Layer + NL -> SQL Guardrails
Jennifer Novak
  • Allyship That Actually Works: Practical Ways to Support Women in Tech
  • Accelerating End-User Adoption: Practical Adoption Change Management for Rapid Technology Rollouts
  • Secrets to Successful Copilot Implementation: From Readiness to ROI
N.J. Robinson
  • 3 Players Every Manager Will Lead: Principles for Developing High-Performing Teams
Siri Yellu
  • Why On-Time Delivery Breaks: Using Data to Understand and Improve Last-Mile Operations
  • Do Hand Crafted Image Features Still Matter? Evaluating Approaches for Cell Nuclei Classification
Dr. Cathy Sarvis
  • Sustaining Performance Without Exhaustion
Sivakumar Dhanasekar
  • Artificial Intelligence in Finance: Risk Management, Fraud Detection, Algorithmic Trading, and RegTe
Navneet Dalipkumar Magotra
  • Scaling Generative AI in the Real World: From Cloud Models to Trusted Intelligent Systems
  • LLM-Driven Voice Agents That Collaboratively Talk To Each Other: Towards Vocal Multi- Agent Systems
Aditya Mulik
  • Data Architecture for Production LLM Systems: Managing Context Cost and Quality at Enterprise Scale
Nihal Kaul
  • When Small Language Models Beat Large Ones in Production
  • How Data Is Stored and Queried Inside a Vector Database
  • Running AI Agents as Data Pipelines in Production
Shamindra Peiris
  • Generative AI for Fraud Analytics
Kapil Sharma
  • Building Agentic AI for Business Analytics with LangChain & LangGraph
Sowjanya Karri
  • Explainable Generative AI Models for Anomaly Detection in Transactional Finance Data
Rajkumar Kuppuswami
  • Smart Research & Academic Assistant
  • Creative + AI Reasoning: Multimodal Narrative Intelligence Engine
  • AI Ethics & Bias Detection Tool (Powered by Google Gemini)
  • Developer & Data Science Tools
  • Supply Chain & Forecasting AI
Smriti Bajaj
  • How Data Looks in a Quantum Computer
Mou Rakshit
  • Real-Time Intelligence: Turning Streaming Data into Smart Decisions
  • AI-Powered Real-Time Intelligence: Transforming Data-Driven Decisions with Microsoft Fabric & GenAI
  • Designing Conversational BI: How Databricks AI/BI Genie Unlocks Self-Service Insights
Shishir Tewari
  • Scalable Customer Lifecycle Intelligence
  • Rearchitecting Financial Data Processing for Petabyte-Scale Allocation
Kayla Boor
  • Accidental friends: how a DBA and an SRE worked together to optimize the system.
John Kerski
  • DataOps 101 – A Better Way to Develop and Deliver Data Analytics
  • Leveraging Large Language Models with Power BI
  • Querying SharePoint Data in Power BI - Options & Performance
  • Querying Power BI REST APIs within a Power BI Dataset
  • What is Power BI Developer Mode?
Sudhir Amin
  • Beyond Traditional DBA Practices - Transforming T-SQL Scripting Expertise into AI Agents
John Miner
  • Many ways to track changes in SQL Server
  • Introduction to the data build tool (dbt)
  • Fabric Data Engineering with Python Notebooks
  • Building a reporting warehouse using Fabric
  • Understanding file formats within the Fabric Lakehouse
Mohamed Mortadha Manai
  • Building Agentic AI Workflows with xAI on Vertex AI: From Code to Action
Jonathan Stewart
  • Fabric Copilot: Consumption and Cost Demystified
  • Ethical Data Storytelling & Visualization Amidst Crisis and Complexity
  • Building Scalable Data Warehouses with Microsoft Fabric:
  • The Fabric Fast Track Workbook: Deploy Enterprise Analytics in 90 Days
Rajesh Vayyala
  • Why Everyone Has Data but No One Trusts It
  • Designing Enterprise Semantic Models for Consistent Analytics
  • Medallion Architecture in Practice: What Data Engineers Should Know
Yamini Pradeepika Rathamsetty
  • AI Career Kickstart: Building Your Future in Machine Learning"
  • "AI Made Simple: Your First Machine Learning Journey"
  • "Agentic AI in Production: Teaching Machines to Learn Without Breaking Everything"
  • From Zero to Cloud Hero: How I Became a Thought Leader (And You Can Too!)
Karunakar Kotha
  • Moving to Azure SQL from VM-based SQL