Call for Speakers

Day of Data SLC 2026

in 3 months

Day of Data SLC 2026

event date

19 Sep 2026

location

Neumont College of Computer Science Salt Lake City, Utah, United States


This event will be IN PERSON only.    

We are planning a Data Saturday SLC.  We hope we will receive a Diverse set of sessions related to any DB system.   All sessions will be held in person at the Neumont College of Computer Science. This will be a 1-day event with sessions throughout the day. The event is free and open to all. 

We welcome tracks from all Database Systems.  

Now is your chance to present and help build and maintain this amazing technical community we have.  It's been too long since we have been able to present in person, and we are planning to put this event on fully in person.

If you need assistance getting a session ready or if you would like to review the presentation with someone, please let us know, and we will happily jump on a Zoom meeting and provide tips and tricks.  

 All sessions right now will be 60 minutes in length.  We will be looking for volunteers to help facilitate conversations on various topics.

Why present? 

  1. Improve your skills and help others.  Presenting allows you to learn something even better than before and in the process, you are helping others to gain information.  
  2. Advocate something you are passionate about.  If you love a technology/topic share it with others!  Passion and drive show during presentations and will also help others see that.  
  3. Name/Services Recognition.  If you are interested in getting more projects in the future or perhaps a new job/different career. Presenting something not only shows how willing you are to learn but you are willing to help others. It is a great addition to any resume to be part of a community. 
  4. Make connections/Network.  Networking is key to moving forward in your career and presenting to others is a great way to build your network since people will want to hear from you. 

Session Selection

How we approach speaker selection. The schedule right now has room for about 30+ sessions. This is a much smaller schedule than we have had in the past so we will be limited in what sessions we can accept this year.  Sessions will be 60 minutes in length we suggest 45 minutes for presentations and 15 minutes for Q&A.  All presenters will only have 1 speaking slot until all presenters have a slot. Once the schedule has been filled we will then go back to the sessions and take second sessions from presenters based ranking of the abstract/presentation. We are planning on having community voting on for the sessions for this event as well. Stay tuned for how that exactly will work. 

I have included an example below to make this clear.

Pat Submitted 3 sessions to speak and the vote breakdown was like this. session1 = 2nd rank, session2 = 3rd rank, session3 =1st rank.

Nick Submitted 2 sessions to speak and the vote breakdown was like this. session1 = 2nd rank, session2 = 1st rank.

Pat would get Session3 placed on the schedule. Nick would then get his session2 placed on the schedule. This would continue through all speakers, after the last speaker had a slot chosen then we would go back and pat would also get session1 for 2nd rank(depending on other speakers and other ranks as well).

One of the primary goals of the event is to grow the speaker community. We encourage you submit to speak.  If you are a new speaker and would like a review of your presentation or help with practicing please contact us below.  We are happy to help you out.  

If you have any additional questions contact 

Pat Wright

pwright@utahgeekevents.com 




open, 23 days left
Call for Speakers
Call opens at 7:00 AM

23 Apr 2026

Call closes at 11:59 PM

06 Jul 2026

Call closes in Mountain Daylight Time (UTC-06:00) timezone.
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all submitted sessions

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56 submissions
Submitted sessions
Jayakumar Ramalingam
  • Real-Time AI Feature Pipelines: From Clickstream to Inference in Production
  • Building Trusted Real-Time Data Products for AI Personalization
Kellyn Gorman
  • AI and Data Protection in Today's World: Data Democratization and AI Security in Microsoft
  • Navigating SQL Server to PostgreSQL Migrations and How DBAs Keep Their Sanity
Zachary Johnson
  • Dataverse: Dataflows
  • Dataverse Virtual Tables
  • Dataverse: Utilizing Views with Power Apps and Power BI
  • Dataverse: A crash course
John Kerski
  • Querying SharePoint Data in Power BI - Options & Performance
  • Modern Semantic Model Testing with DAX, UDFs, and AI
  • DataOps 101 – A Better Way to Develop and Deliver Data Analytics
  • Leveraging Large Language Models with Power BI
Praparna Moharana
  • Automating Healthcare Compliance Reporting with SQL, Python, and Power BI
Jeff Foushee
  • The T-SQL JSON Index
  • The T-SQL JSON Operators
  • The T-SQL PIVOT/UNPIVOT Operators
Steve Seeley
  • I am a Data Engineer. Do I need to be concerned about AI?
Serhii Savin
  • Mastering Geospatial SQL: High-Performance Spatial Analytics at Scale
Karunakar Kotha, Shankar Narayanan SGS
  • From DBA to AI Engineer: The Future of Data Careers
  • Building Enterprise RAG Applications Inside SQL Server
  • SQL Server 2025 + Microsoft Fabric: Building AI-Native Data Platforms
  • Agentic DBA Copilot: Autonomous Operations for SQL Server at Scale
Shari Oswald
  • From Flat to Fabulous: Reshape Your Excel Data into a Powerful Data Model
show all submissions
Andrew Madson
  • The Who, What, and Why of Data Lake Table Formats
  • Building AI-Native Data Pipelines
  • AI Ready Data with Apache Iceberg: Unifying, Controlling, and Optimizing Your Data for Effective AI
  • Iceberg for Agents - Turning Lakehouse Data Into AI-Ready Context
Chetan Nandikanti, Alvaro Costa-Neto
  • Autonomous Database Operations using Agentic AI for SQL Server
McKay Salisbury
  • Database normalization - and getting to good design
  • Protect Yer Data From Scallywags With Zero-Trust Zero-Latency Security (In Pirate)
Sudhir Saxena
  • Serverless Data Architectures for Scalable AI and Cloud Applications
Dave Stokes
  • Structured Query Language In Fifty Minutes
  • Can An AI Assistant Help You With Your Database Chores?
Aaron Cutshall, DHA, MSHI
  • A Postgres Developer's Snowflake Survival Guide
  • A Practical Guide to Set-Based Queries
  • Tech Debt: Causes, Effects, and Solutions
  • Leadership Essentials for Data Teams
Joy Curtis
  • Scaling Impact: Leading 100 Interns to Deliver Real-World AI at Speed
  • Leading When You’re Not the Expert: Context Before Control in Cross-Cultural Work
  • AI Beyond the Sales Pitch: The Gap Between Experts
Vinay SIddhavanahalli Ramakrishna Rao
  • Green Cloud Computing: Sustainable Strategies for Private Cloud Operations
Varun Joshi
  • Scaling Data Governance in Redshift:Automating quality check and lineage in high-volume data.
  • Generating Data That Doesn't Exist: How Synthetic Data Is Solving the Privacy-Utility Tradeoff
  • From ETL to Autonomous Pipelines — The Future of Data Engineering on AWS
  • Why most LLM systems break in system and how to fix them.
Alvaro Costa-Neto
  • Mastering PostgreSQL: Advanced Techniques for SQL Server DBAs
Umamaheswara Rao Kukkala
  • Transforming Legacy Data Warehouses into AI-Enabled Modern Data Platforms Using BigQuery
Maheshkumar Mole
  • Building Scalable Data Platforms for High Accuracy Predictive Analytics
Balazs Horvath
  • The AI is ready, but you are the problem. How to finally be ready for a real AI.
  • We gave AI twelve weeks to build the perfect employee: We will never need to hire a senior again
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  • Microsoft talks about Frontier Firms. We are building one: A case study from the trenches.
Mou Rakshit
  • AI-Powered Real-Time Intelligence: Transforming Data-Driven Decisions with Microsoft Fabric & GenAI
  • From Data to Decisions: Building Agentic Construction Intel using Azure Databricks Agent Bricks
  • Designing Conversational BI: How Azure Databricks AI/BI Genie Unlocks Self-Service Insights
  • Agentic AI in Finance: Governed Metrics, Open Access, and Automated Action on Azure Databricks