CI/CD Magic: Unlocking the Power of Microsoft Fabric

Supercharge your CI/CD game with Microsoft Fabric! Get ready to transform your workflows and say goodbye to development headaches. This session dives into the magic of Git integration and deployment pipelines—making teamwork a breeze and efficiency your new best friend.

Explore Git’s Grimoire: branching like a pro, mastering pull requests, and nailing code reviews. It’s all about boosting collaboration, keeping everyone accountable, and ensuring your code evolves with your needs. From development to testing to production, we’ll show you how to make those pipeline transitions feel like a well-choreographed dance.

And, yes, we’re not skipping the quirks—because every spell has its downside. Microsoft Fabric might have a few eccentricities, but with these expert tips and workarounds, you’ll handle them like a champ.

Whether you're a coding mage, a solution architect extraordinaire, or just curious about the latest in CI/CD wizardry, this session will leave you armed with the know-how to future-proof your projects.

Power BI - Performing Data Quality Checks Using Python & SQL

Picture this, you have a report in Power BI that someone passes off to you for data quality checks. Simple enough until they clarify they need every measure checked against the source database.
There are a few ways to make sure the measures match what is in the source data system, but you need something easily repeatable and self documenting. In this presentation, I will walk through how to use python and excel to perform our data quality checks in one batch and document any differences. In order to do that, we are going to build a python script that can run Power BI REST APIs, connect to a SQL Server, and read/write to Excel.
By the end of this session, attendees will have a plug and play tool to check data from SQL against Power BI.

Internet is required

Exploring Real-Time Horizons with Microsoft Fabric

Blast off into the future of analytics with this interstellar session on real-time data processing in Microsoft Fabric!

From setting up KQL databases to capturing data streams from the International Space Station (yes, really!), this session is packed with hands-on tips and tricks. You'll explore how to harness the power of Event Streams and Logic Apps to create a seamless data pipeline that fuels real-time Power BI reports.

Discover the basics of KQL—spoiler alert, it’s not SQL! Learn to query data like a tabular astronaut, watching your dashboards come to life with up-to-the-minute updates. With step-by-step guidance and plenty of cosmic creativity, you'll master real-time analytics faster than a rocket launch.

Whether you're a data explorer, a real-time analytics enthusiast, or just curious about real-time tracking space missions, this session is your ticket to the stars. Prepare for liftoff as we explore how Microsoft Fabric can transform your streaming data into celestial insights.

Power BI - How to Fix an Inherited Report

A common request in the realm of reporting is "hey, we have this report that a previous VIP used, but the report is really slow and the new VIP would like to revamp the report to answer their questions". Great, you think, I can knock this out no problem! Then, you open the report. Fifty tables, over a hundred measures, and six calculated tables later you start to panic.
This session will go into best practices for dissecting a complicated report and a checklist for quick wins. No need to panic, this session will help build a toolbelt to tackle any reconstruction project.

Power BI Meets Programmability – TOM, XMLA, C#, and TMDL

It is rare to find a Power BI developer who has a background in C#, but C# and other programming languages offer a lot of automation and scalability that is lacking in Power BI. XMLA is a powerful tool available in the online Power BI service that allows report developers to connect to their data model and adjust a variety of entities outside the Power BI Desktop application. For example, the XMLA endpoints can be used within a pipeline triggered by an application to update a Power BI model schema. This allows end users to create custom UDFs (user defined fields) on the fly and delete them. Similarly, developers can create and use translations for customer specific column renames without worrying about breaking visuals and complicated data models.

Power BI - Creating a M-agical Date Table

By the end of this session, attendees will have a deeper understanding of how to manipulate M code in Power BI through the process of building a highly customized date table.

Many times Power BI developers get caught between DAX and SQL when they need the flexibility of DAX but the performance benefits of SQL, which leaves them in the land of M. Similar to Oz, M is full of magic that is more attainable than meets the eye. This session demystifies the functionality of Power Query and covers when Power Query may be the best option.

Mastering Data Quality Validation in Fabric for Power BI Reports

Picture this: you’ve just inherited a Power BI report, and your task is to perform data quality checks. Simple enough, until you’re told that every measure in the report must be validated against the source database. Suddenly, what seemed like a straightforward task becomes a time-intensive challenge.

There are several ways to ensure the measures align with the source data, but the process needs to be efficient, repeatable, and, most importantly, self-documenting.

In this session, we'll walk through using Python notebooks in Microsoft Fabric to streamline the data quality validation process. Together, we’ll build a Python script that performs these checks in a single batch and logs any discrepancies for review. You’ll learn how to:
- Utilize Power BI REST APIs to access measures dynamically.
- Connect to a SQL Server database for real-time validation.
- Create a logging table to document differences automatically.

This method ensures consistency, saves time, and provides a clear audit trail for every data quality check. Whether you’re a data engineer or analyst, this hands-on approach will empower you to handle even the most complex validation tasks with ease.

Power BI Admin Level-Up: Leveraging Fabric to Manage Your Tenant

Have you ever wanted to build a custom usage metric report for your Power BI tenant, but didn’t know where to start? Or perhaps you’re a Power BI admin eager to explore how Microsoft Fabric can transform your workflows? If so, this session is exactly what you’ve been looking for!

In this hands-on session, I'll take you step-by-step through building a powerful usage metrics, access auditing, and semantic model failure exploration using Microsoft Fabric. You’ll learn how to create a Python notebook in Fabric that interacts with the Power BI REST APIs to pull critical tenant data like semantic model refreshes, workspace access, and usage. From there, we’ll learn how to structure and load this data into a Fabric Lakehouse, making it accessible for dynamic reporting.

But this session is more than just a technical tutorial, it’s about empowering you with the tools and techniques to unlock new possibilities for monitoring and optimizing your Power BI environment. By the end, you’ll have not only a fully functional monitoring report but also a clear understanding of how Fabric can revolutionize the way you manage and report on your Power BI tenant.

Mastering Microsoft Fabric Data Warehousing: Tips & Tricks You Need to Know

During this session, we’ll dive into a range of helpful tips and tricks that I wish I had known when starting out with Microsoft Fabric data warehouses. These insights are designed to save you time, optimize performance, and make managing your data warehouse more efficient.

We’ll start by exploring a clever trick to create a case-insensitive warehouse using a simple API call, a small adjustment that can have a significant impact on query consistency and usability. From there, we’ll tackle performance monitoring, focusing on identifying and addressing slow queries. You’ll learn how to leverage built-in tools and techniques to pinpoint bottlenecks and take corrective action.

But what happens when a rogue query threatens to cripple your capacity? Don’t worry, we’ll cover how to detect and kill capacity-destroying queries before they disrupt operations. This critical skill will ensure your data warehouse remains stable and responsive, even under heavy workloads.

Throughout the session, I’ll share practical, real-world examples and actionable strategies to help you get the most out of Microsoft Fabric. Whether you’re new to data warehousing or looking to sharpen your skills, this session is packed with valuable insights you can start using immediately.

Decoding Fabric Licensing

Embark on a journey through the layered landscape of Microsoft Fabric licensing, where cryptic SKUs, hidden costs, and mysterious capacities await. This session sheds light on the most misunderstood parts of the licensing maze, using real-world examples to bring clarity to the chaos. Whether you’re just starting to explore or deep into discovery, you’ll leave with the map you need to make confident, cost-savvy decisions.

Attendees of this session will leave knowing how to:
- Distinguish between Power BI Pro, Premium Per User (PPU), and Fabric SKUs
- Choose between Pay-As-You-Go and Reserved pricing (and when it matters)
- Estimate licensing costs with real-world scenarios and user personas
- Match capacity sizes (F SKUs) to your org’s workloads and needs
- Avoid common budgeting pitfalls and over-provisioning traps

Notebook Ninja: Best Practices for Building Reusable, Scalable Fabric Notebooks

Notebooks in Microsoft Fabric aren’t just for one-off scripts. They can be powerful, reusable, and modular building blocks in your data workflows. In this session, we’ll walk through best practices for building and organizing Fabric notebooks like a pro. Learn how to chain multiple notebooks using DAG-style execution, call notebooks with parameters and UDFs, and manage code reuse like a well-oiled data ops team. Whether you're orchestrating data engineering workflows or building shared libraries for your team, this session will give you the tools and patterns you need to level up your notebook game.

The Fellowship of the Star Schema: Transforming OLTP Data for Power BI

One does not simply build reports on OLTP data. Join us on an epic journey from the depths of raw, normalized tables to the shining halls of a well-modeled star schema fit for Power BI greatness. We’ll demystify the differences between OLTP and OLAP, reveal the secrets of dimensional modeling, and show you how to forge relationships (and maybe even a few Slowly Changing Dimensions) that rule them all. Whether you’re a data wizard, a curious hobbit, or somewhere in between, you’ll walk away with practical techniques to build models that are as powerful as the One Ring but far less corrupting.

Mastering the Content Snowball - Turning Tiny Efforts into Big Opportunities

Speaking and blogging can be extremely intimidating, especially in the face of imposter syndrome, perfectionism, and limited free time. But community visibility compounds opportunities for jobs, meeting amazing people, and traveling the world, so how can we overcome those fears to get to the good stuff?

Breaking into the data community doesn’t require a huge following or a million unique ideas, it only requires passion and consistency. To tackle those common blockers, we'll utilize a number of concepts including the Content Snowball, the Tiny Topic Picker, and the LEGO Method of creating new shapes with the same blocks.

By the end of this session, attendees will know how to:
- Pick a topic
- Set up a free blog
- Craft presentations for conferences
- Submit sessions
- Establish patterns of posting to build your presence in the data community
- Measure meaningful KPIs
- Keep the passion alive

This session is for everyone who is looking to get off the starting block or past a plateau. Bring all your concerns and questions about getting involved in this incredible data community.

Modern Data Warehousing with Microsoft Fabric: Patterns, Practices, and Pitfalls

In the age of cloud analytics, today’s best practice is tomorrow’s legacy. Microsoft Fabric aims to be the one platform that rules them all, bringing together data engineering, warehousing, and visualization in a single Software-as-a-Service (SaaS) package. At the heart of this platform, Fabric Data Warehouse delivers a familiar yet modern T-SQL–based experience that is scalable, cloud-native, and tightly integrated with the broader Fabric ecosystem. It supports multiple ingestion and transformation paths. It provides practitioners flexibility with how data is landed and shaped whether streaming, batch, or metadata-driven. Just as importantly, Fabric data warehouse is designed to serve not just as a single central repository, but as a collection of purpose-built warehouses that can coexist and scale within an environment, aligning with both technical best practices and business needs. With its seamless integration to Power BI, Fabric empowers data professionals to shorten the path from raw data to actionable insights, while providing the governance and lifecycle tools needed to manage growth and change over time.

The landscape of data roles and technologies is rapidly shifting. Many professionals find themselves as “accidental” data warehouse practitioners that are tasked with designing and implementing warehouses without formal training, simply because the responsibility landed on their desk. At the same time, long-standing on-premises data warehouses are being retired in favor of cloud-native platforms, and Power BI datamarts are being phased out with Fabric Data Warehouse emerging as the recommended successor. Together, these changes are reshaping how organizations think about their data architecture and how individuals must adapt their skills to thrive in a modern analytics environment.

The presenters are experienced data warehousing practitioners who will guide attendees through the patterns, practices, and pitfalls of Microsoft’s modern approach to data warehousing in Fabric. Drawing on real-world expertise, they will highlight both the opportunities and the challenges of adopting Fabric DW, from modeling fundamentals to ingestion strategies and lifecycle management. Attendees will leave the session with a clear understanding of how to design and manage effective warehouses in Fabric, avoid common mistakes, and apply proven techniques that accelerate success in their own environments.

Contents:
• Part 1 - Patterns: Dimensional data modeling
• Part 2 - Patterns: Data Warehousing fundamentals
• Part 3 - Patterns: Ingestion and medallion architecture
• Part 4 - Practices: Change detection
• Part 5 - Practices: Data warehouse life cycle and CI/CD
• Part 6 - Practices: Monitoring and administration
• Part 7 - Practices: Migrations
• Part 8 - Pitfalls: Tips and tricks on how to avoid them

Intended Audience:
• "Accidental" data warehousing professionals, or those looking for a refresher on the theory and techniques of data warehousing in Fabric.
• Folks needing to migrate from an on-premises data warehouse or from Power BI datamarts to Fabric.
• The focus is on data warehouse development and data engineering. The content may be less applicable for those whose primary role is report building and/or data analysis.
• The content is aimed at the doers, not the delegators.

Modern Data Warehousing with Microsoft Fabric: Patterns, Practices, and Pitfalls

In the age of cloud analytics, today’s best practice is tomorrow’s legacy. Microsoft Fabric positions itself as the rebel alliance to this chaos, a single platform uniting data engineering, warehousing, and visualization in one SaaS package. Within this universe, the Fabric Data Warehouse awakens as a powerful yet approachable force: a T-SQL–based engine that works seamlessly with multiple ingestion and transformation patterns, from batch loads to streaming flows. But unlike the Death Star, this isn’t about building one massive monolith. The true power lies in creating multiple purpose-built warehouses that coexist, scale, and adapt to your business needs. With native integration to Power BI, Fabric makes it easier for practitioners to bring order to their data galaxy, while avoiding the dark side of accidental complexity.

The data galaxy is in flux, and with it, the roles of those who navigate it. Many have become “accidental” data warehouse practitioners through volunteering (or perhaps being voluntold) to build warehouses without the benefit of a proper training academy. Meanwhile, the old on-prem strongholds are fading into legend as organizations make the jump to cloud hyperspace. Even Power BI datamarts, once a trusty starfighter for quick solutions, are being decommissioned, with Fabric Data Warehouse now the recommended vessel for the battles ahead. For data professionals, this isn’t just a shift in tooling. It’s a new chapter in the saga, where adapting to change determines whether you stay a padawan or become a true Fabric master.

The presenters are seasoned data warehouse Jedi, ready to share the patterns, practices, and pitfalls of Microsoft’s modern approach to data warehousing in Fabric. Through demos and stories from the trenches, they’ll illuminate both the light side (what works well) and the dark side (what to avoid) of Fabric DW, covering everything from modeling to ingestion to lifecycle management. Attendees will leave the session equipped with their own lightsaber of knowledge, prepared to build, monitor, and scale Fabric warehouses without falling victim to the traps of accidental complexity.

Contents:
• Part 1 - Patterns: Dimensional data modeling
• Part 2 - Patterns: Data Warehousing fundamentals
• Part 3 - Patterns: Ingestion and medallion architecture
• Part 4 - Practices: Change detection
• Part 5 - Practices: Data warehouse life cycle and CI/CD
• Part 6 - Practices: Monitoring and administration
• Part 7 - Practices: Migrations
• Part 8 - Pitfalls: Tips and tricks on how to avoid them

Intended Audience:
• "Accidental" data warehousing professionals, or those looking for a refresher on the theory and techniques of data warehousing in Fabric.
• Folks needing to migrate from an on-premises data warehouse or from Power BI datamarts to Fabric.
• The focus is on data warehouse development and data engineering. The content may be less applicable for those whose primary role is report building and/or data analysis.
• The content is aimed at the doers, not the delegators.