Call for Speakers

in 4 months

SQLDay Lite 2026

event starts

24 Sep 2026

event ends

25 Sep 2026

location

Politechnika Gdańska, Budynek B Wydziału Elektroniki i Informatyki Gdańsk, Poland

website

sqldaylite.pl/

It's another fabulous edition of SQLDay Lite in Poland. It's in-person event only, community-oriented and a bit smaller than the original SQLDay. SQLDay Lite, in scale is closer to SQL Saturday or Data Saturday events happened in previous years in Poland.

Have a topic burning in your mind? Share it with us! Submit your session ideas in the “data” field, and let’s make the return of SQLDay Lite unforgettable! We are skewed towards Microsoft technology stack but we always include other vendors in our agendas.

Event organizer is Data Community Poland - your friend in data for almost 20 years.

Join us, and let’s create new memories together! 

open, 53 days left
Call for Speakers
Call opens at 9:00 AM

12 May 2026

Call closes at 11:59 PM

31 Jul 2026

Add to calendar
Call closes in Central European Daylight Time (UTC+02:00) timezone.
Closing time in your timezone () is .

The call for speaker is split into two parts:

  • Pre-con workshops (8h) - submissions until 30.06.2026
  • Technical sessions (45 min) - submissions until 31.07.2026
  • Keynote (20 min) - submissions until 31.07.2026


All sessions are in person for speakers and in-person for attendees. We are planning 8-hour pre-con training sessions and 45-minutes breakout sessions - all data related. Whether it is on-premises or in the cloud. ETL or AI. Architecture or database engine deep-dive. Programming or administration. All topics welcome.

For pre-con workshops, we prefer them to include hands-on labs.

Session/workshop language: polish or english


all submitted sessions

publicly listed on this page

accommodation

expenses covered

event fee

free for speakers

1 night for general session speakers, 2 nights for pre-con speakers

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28 submissions
Submitted sessions
Jonathan Burger
  • From Excel Snapshots to Trusted BI: Change Ledgers and Semantic Models Without a Warehouse Budget
Jose Manuel Jurado Diaz, Juan Moreno Romo
  • Resilient, Scalable Data Management with Azure SQL Hyperscale for Devs and DBAs
  • SSMS Copilot to the Rescue – Integrating AI into Your Daily DBA Work
Tomasz Libera, Michał Sadowski
  • AI-ready SQL Server 2025: praktyczne warsztaty z vector search, JSON, regex i Fabric
Nick Holt
  • Bigger and Wider is Better
Kristian Johannesen
  • Semantic Models and Databricks: Learnings from the field
  • Genie in a bottle: An introduction to Conversational BI on Databricks
Uwe Ricken
  • How to properly handle LOB data in SQL Server
  • Security techniques for cross database access
  • The strengths of partitioning – practical examples
  • Mastering Statistics in Microsoft SQL Server
  • How Intelligent Query Processing (IQP) can help reduce cloud costs
  • Improve your skills as a professional DBA
  • SQL Performance Pitfalls: Identification and Optimization Lab
Dominik Szcześniak
  • AI Meets Power BI: Practical MCP Server & AI Use Cases Beyond Development
  • Slim Models, Lower Bills: Cutting Power BI/ Fabric Capacity Costs from the Inside
Federico Fregosi
  • Scalable, Flexible, and Cost-Effective Data Lakes: Open-Source Solutions for Modern Data Management
Mateusz Osiak
  • Medallion Architecture w dużej organizacji: więcej niż Bronze, Silver i Gold
Mladen Prajdic
  • Social Engineering: Hacking People
  • SQL Server Accelerated Database Recovery
  • Thē wönderfűl wôrld of ćollåtions, eñcodingß and téxt sţoræge
  • SQL Server 2025 Optimized Locking
show all submissions
Lukasz Grala
  • AI pod lupą: Jak nie utopić projektu w morzu hype'u.
Maciej Szymkowski
  • Can we trust LLMs?
Jakub Wawrzyniak
  • Operacjonalizacja procesów biznesowych z Microsoft Fabric IQ
  • Azure HorizonDB: nowa generacja rozproszonych baz danych w architekturach cloud‑native
Joanna Hryniewicz
  • Your Data Platform Is Overweight: A Biohacker’s Guide to Cutting Fabric Fat Without Losing Strength
  • The Nervous System of Modern Teams: Coaching in the Age of AI