SQL Day 2026

If you’ve ever been frustrated by a test database filled with nonsense, duplicates, sensitive information, or YOLO-style restored production backups, this session is for you.

Join Peter Kruis and Tonie Huizer, two energetic data enthusiasts, on an epic (and slightly chaotic) quest to build test databases that are safe, realistic, and actually useful for development and testing. With decades of combined experience, they’ll take you on a journey through the wild world of test data, showing just how bad it can get, and how good it can be.

Through engaging role play, real-world examples, and live demos, they’ll expose the dangers of shady test environments and share smarter, safer ways to manage test data. Audience participation is encouraged; because (bad) test databases are a team sport!

You’ll leave entertained, but more importantly, you’ll leave with tools and strategies to stop your test database from being the weakest link in your development chain.
Because let’s face it: your test database shouldn’t suck.

❓ Have you been using PowerBI for a while but your users are now asking for more complex measures and reports?
❓ Would you like to step beyond these simple reports and take your DAX to the next level to solve your organisation’s challenges?
❓Are you comfortable with basic DAX and CALCULATE, but:

Seeking solutions to complex business problems using DAX.
Working in industries like finance, sales, supply chain, or analytics, where advanced calculations are essential.
Your DAX is limited and you end up with solutions that don’t perform.
You solve problems by duplicating and precalculating data – which is slow to iterate on – rather than in DAX.
You are looking forward to review several DAX concepts with practical applications you can easily reuse.
You want more DAX tools in your DAX toolbox to help you excel.

Overview
This workshop will advance your DAX skills to bridge the gap between basic and advanced concepts. Through real-world scenarios, you’ll learn to write efficient expressions, solve complex business challenges, and create dynamic, impactful reports with DAX.
Here are a few examples of what you can learn in this workshop:
✅Using OR conditions between slicers in DAX.
✅Creating a slicer that filters multiple columns in Power BI.
✅Learn how to use REMOVEFILTER / VALUES for “natural” hierarchical calculations.
✅Show updated year-to-date actuals and forecasts in the same chart.
✅When and how to use visual calculations in DAX.
✅Optimize cumulative totals using variables and windows.
✅Implement different types of ranking calculations.
✅Aggregate relative periods (like each new customer’s first 30 days of purchase) efficiently.

Warsztat przeprowadzi uczestników przez cały cykl życia modeli uczenia maszynowego – od budowy danych, przez trening i automatyzację, aż po wykorzystanie potencjału AI w rozwiązaniach produkcyjnych. Uczestnicy poznają pełny stack MLOps oparty na środowisku Databricks oraz MLFlow, nauczą się projektować pipeline’y, przygotowywać dane, tworzyć cechy, trenować modele, wdrażać je i monitorować w realnym środowisku.

Warsztat stawia na konkret: praktyczne podejście do architektury ML, feature engineeringu, klasycznych algorytmów, sieci neuronowych i głębokich, CI/CD dla modeli, MLOps i nowoczesnych rozwiązań z obszaru AI. Uczestnicy wyjdą z niego z kompletnym obrazem, jak projektować i utrzymywać systemy ML, które działają, skalują się i nie wybuchają w produkcji.

Zakres warsztatu:
1. Architektura AI/ML – pełny obraz stacku ML, role w procesie i referencyjne architektury chmurowe.
2. Dane – praktyczne przygotowanie, czyszczenie, walidacja i budowanie pipeline’ów.
3. Feature engineering – typy cech, transformacje, feature store, monitoring i drift.
4. Algorytmy ML – przegląd najważniejszych metod i ich zastosowanie w praktyce.
5. Trenowanie modeli – metryki, tuning, podejście distributed, MLflow w akcji.
6. Sieci neuronowe i Deep Learning – podstawy sieci, frameworki, skalowanie, GPU/TPU.
7. Pipeline ML – automatyzacja, CI/CD, orkiestracja i wersjonowanie modeli.
8. MLOps – pełne utrzymanie modeli, monitorowanie, testy, rejestry modeli.

Warsztat jest kierowany do inżynierów, data scientistów i architektów pracujących lub planujących zacząć pracę z ML.

Wymagania:
– Laptop z przeglądarką internetową
– Darmowe konto Databricks Free

This hands-on lab workshop is designed for professionals who want to master building AI agents using Microsoft Copilot Studio.
Participants will spend 80% of the time in practical labs, creating intelligent agents that automate workflows, process multimodal inputs, and deliver dynamic, data-driven responses.

Key Highlights:
– Build and customise agents using Copilot Studio authoring tools
– Implement Dataverse grounding for real-time accuracy
– Design multimodal prompts for richer user experiences
– Configure autonomous event triggers for proactive agent behaviour
– Learn best practices for responsible AI and governance

Agenda:
– Building agents in Copilot Studio
– Building multi-agent systems
– Building autonomous agents
– Customising agent responses
– Applying responsible AI and content governance
– Implementing multimodal features
– Augmenting prompts with grounding

Pre-Built Assets Provided:
– Agent flows
– Prompt templates
– Sample data and solutions
These assets ensure participants can complete all labs quickly and successfully.

Prerequisites:
– Laptop running Windows 11
– Microsoft Edge browser
– Free trial of Microsoft Copilot Studio

You’ve seen it before: the procedure that looks like it was generated by an AI trained on Stack Overflow and despair. It’s got MERGE. It’s got RIGHT JOINs. It’s got logic so tangled you’d need a flowchart, a flashlight, and a therapist to debug it. And now… it’s your problem.

In this full-day festival of query-fixing, Erik Darling leads you through the real world mysteries of advanced T-SQL: the strange, the slow, and the occasionally cursed. You’ll tackle tangled paging logic, rescue window functions and indexed views from spools and spills, and finally learn when to keep a CTE and when to yeet it. We’ll refactor data modifications that block like linebackers, decode procedural patterns, and write dynamic SQL that’s powerful and polite.

You’ll learn when to CROSS APPLY, dig into views vs. inline TVFs, and discover why RIGHT JOIN is not simply LEFT JOIN’s syntactic twin. We’ll uncover when user-defined functions wreck your query execution plans—and how to rewrite them with flair. If you’ve ever been curious about why that query sometimes takes SO long and how to best rewrite it without just guessing, this is your playground.

Expect fast demos, big laughs, and a glorious cheat sheet to take home. Because refactoring SQL isn’t just necessary—it’s super fun when you’re in the right party.

Are you ready to take a deep dive into PostgreSQL and expand your expertise beyond SQL Server? This one-day, hands-on precon workshop is designed for SQL Server developers and DBAs who want to fully understand PostgreSQL and its distinct architecture, concepts, and best practices.

In this intensive workshop, we’ll explore PostgreSQL’s unique features and how they differ from SQL Server. You’ll gain a comprehensive understanding of fundamental concepts such as table structures, indexing, and performance optimization, while also delving into PostgreSQL-specific features like MVCC (Multiversion Concurrency Control), VACUUM for space management, and TOAST (The Oversized Attribute Storage Technique) for handling large data.

Throughout the day, expect deep dives into:

• Transaction isolation levels and how PostgreSQL’s MVCC ensures consistent reads and writes.
• Effective use of VACUUM to manage storage and prevent table bloat.
• Partitioning strategies and indexing methods unique to PostgreSQL.
• PostgreSQL’s approach to replication and clustering, in contrast to SQL Server’s AlwaysOn Availability Groups and replication.

This workshop emphasizes practical, real-world scenarios with numerous demos and exercises to reinforce learning. You’ll see how to translate your SQL Server experience into PostgreSQL, recognizing where concepts align and where adjustments are needed for PostgreSQL’s environment.

By the end of the day, you’ll not only understand PostgreSQL’s capabilities but also be prepared to apply this knowledge in production environments. This workshop is ideal for those who want a deep, technical understanding of PostgreSQL and how it compares to SQL Server, with a focus on optimizing database performance, data management, and scalability.

Join this full-day, hands-on workshop designed to help you master automation in Microsoft Fabric. Whether you’re starting your automation journey or optimizing existing processes, this session will equip you with practical skills to accelerate development, minimise risk, and reduce costs through low-code and pro-code automation.
You’ll learn how to automate every step of the Fabric Data Platform lifecycle, from design and setup to implementation, deployment, and documentation. Through demo-packed exercises, we’ll guide you in building a robust, scalable, and efficient data platform using automation best practices.

By the end of this workshop, you will be able to:
Automate platform setup using code and configuration scripts.
Implement a metadata-driven ingestion approach for streamlined data preparation.
Build a foundation for semantic models with automation techniques.
Integrate CI/CD pipelines using GitHub and Azure DevOps for continuous delivery.
Leverage Fabric CLI, REST APIs, and the fabric-cicd Python library to simplify workflows.

This workshop blends low-code flexibility with pro-code power, ensuring you leave with actionable tools, scripts, and knowledge to integrate automation into your Fabric Data Platform. From blueprint to reality, you’ll gain the confidence to automate processes that accelerate development and deliver consistent, cost-effective solutions.