• Are we still writing code? How a Data Engineers’ work changed overnight.

    Not long ago we wrote Python, Yaml, SQL, Terraform, you name it. Depending on your stack of course. And we had to know about cloud networking, APIs, data modelling, security.

    The architecture of a decent data lake is broad, we have to know a lot of things about a lot of things. And I didn’t even want to mention machine learning, Power BI modelling and Datavault (yikes).

    Our jobs were demanding, we couldn’t keep up. Changes in the sources broke a pipeline regularly.

    Until suddenly everything changed and we only had to know…. Markdown…. Really ?! Well sort of.

    I am definitely talking to Claude a lot these days and haven’t written much code myself lateley.
    Has it made me more productive, getting more done with higher quality output. Absolutely!
    Did my job become easier and is thinking optional now, can I chill at the coffee machine while Claude spits out everything I need. Definitely NOT!

    My brain is on high alert. The code is not the bottle neck anymore. There’s more of it though and it’s more complicated. I have to be very specific about what I want (and how a lot)

    My job has shifted to quality control, architecture, security. And I’m asked to do more myself, the silos are slowly disappearing.

    And on top of that I have to learn this new skill (pun intended). How do I make sure it’s safe? How does it remember? How do you make skills, how big should a context window be, which model is good for what, do I need local models and are they good enough?

    I’m going to show what I do and how, there will be lessons learned out of my day job. What worked, what didn’t. What got better so quickly you may have discarded it half a year ago, but should try again perhaps.

    ACP (Flamenco)
    Mon 9:15 am - 10:15 am
    • English
    • Intermediate

  • Automating data delivery in Microsoft Fabric – A metadata-driven approach

    As organizations mature their Microsoft Fabric platform, standard reports and curated semantic models are often no longer enough. Business teams want greater flexibility. They want to build their own semantic models, create departmental data products, and work directly with curated data. The challenge is enabling that freedom without compromising governance, security, or the integrity of your central platform.

    This session is based on a real-world Fabric implementation where we built a fully automated, metadata-driven solution that provisions and maintains departmental workspaces. Instead of granting users direct access to central lakehouses, the solution creates dedicated workspaces with the correct lakehouses, shortcuts, permissions, security groups, and settings, all driven by metadata and kept continuously in sync.

    We'll explore the overall architecture before diving into the implementation. You'll see how metadata defines the desired environment, how Spark and the Fabric REST APIs compare the desired state with the current tenant configuration, and how the solution automatically creates or updates workspaces, shortcuts, permissions, and configuration whenever changes are required.

    Along the way we'll discuss the required API permissions, service principal considerations, common pitfalls, and the lessons learned from implementing the solution in production. Although our implementation is Spark-based, the concepts apply equally well to any technology capable of calling the Fabric APIs.

    After this session you'll understand how to automate secure data delivery in Microsoft Fabric, how to build a scalable metadata-driven provisioning solution, which Fabric APIs are involved, and how to give business users the flexibility they need without sacrificing governance or control.

    Foxtrott
    Mon 9:15 am - 10:15 am
    • English
    • Advanced

  • Beyond Source Control: Using GitHub Projects to plan and execute your data projects

    GitHub is no longer just a platform for source control — it has evolved into a powerful collaboration and project management tool as well.

    In this session, we’ll explore how GitHub Projects can help organize your teams work and plans, improve collaboration, and create more transparant progress reports. In addition, we will also identify other areas where Github Projects can improve feedback loops from end users and improve time efficiency both for the developers and the project team lead.

    Let's jump in with both feet and get your team started with GitHub Projects!

    Ballerina
    Mon 9:15 am - 10:15 am
    • English
    • Intermediate

  • Building AI Data Agents in Microsoft Fabric: From Raw Data to Context-Aware Answers

    As organizations adopt AI on top of their data platforms, a common expectation emerges: ask a business question and get a reliable answer. In practice, this often fails - not because of the model, but because the underlying data lacks structure, context, and quality.
    In this session, we focus on Microsoft Fabric as the foundation for building AI-driven data experiences. You will see how data in Fabric Lakehouse and Warehouse can be structured and enriched with business context to make it understandable not only for people, but also for AI.
    Building on this foundation, we will explore how to create AI Data Agents in Microsoft Fabric that can interpret and answer real business questions. We will highlight common challenges such as ambiguous metrics, missing relationships, and inconsistent definitions - and show how they directly impact the quality of AI-generated answers.
    Through a practical demonstration, you will see how the same question can lead to very different results depending on how data is prepared and structured.
    Finally, we briefly extend this approach to AI Foundry, showing how multi-level agent architectures can build on top of Fabric Data Agents to handle more complex scenarios.
    You will gain practical insights into how data structure and context influence AI agent behavior, along with concrete examples from Microsoft Fabric.

    Concerto
    Mon 9:15 am - 10:15 am
    • English
    • Intermediate

  • Building Data Literacy in the Microsoft Data Platform Era

    In today’s data-driven organizations, the ability to interpret, communicate, and make informed decisions with data has become as fundamental as technical infrastructure itself.
    Yet, while many enterprises invest heavily in platforms like Microsoft Fabric and Power BI, the full potential of these technologies is only realized when users across all levels possess a strong foundation in data literacy.
    This session explores how to cultivate, measure, and sustain data literacy within an organization that builds its analytical ecosystem on the Microsoft Data Platform.
    We dive into the basics of Data Literacy, check Best Practises and give some tips how to measure with data support from tools like FUAM.

    Symphonia
    Mon 9:15 am - 10:15 am
    • English
    • Introduction

  • Building Private, Always-Current RAG Pipelines and Semantic Search with SQL Server

    In this session, we'll build a complete local RAG pipeline using .NET and SQL Server.
    A .NET service monitors local network sources, ingests documents like invoices and contracts, generates embeddings via a local LLM,
    and stores them using SQL Server's vector data type. The pipeline also embeds existing relational table data,
    unifying structured and unstructured content into a single semantic search space
    while SQL Server's vector indexes deliver extremely fast similarity search across this unified space.

    Menuett
    Mon 9:15 am - 10:15 am
    • English
    • Advanced

  • Practicing Positive Selfishness - protecting our mental health and well-being

    As IT professionals, we're constantly adapting to change.
    This session explores the idea of positive selfishness: the importance of looking after your own mental health and well-being without feeling guilty about it.

    New technologies, platforms, security challenges, certifications, ways of working and, of course, the ongoing conversation about AI and what it means for our future.
    The pressure to keep up can feel relentless.

    We'll discuss some of the common pressures faced by people working in technology, how they can affect us over time, and why taking care of ourselves is not a luxury, but a necessity.

    Through practical advice, real-world experiences, and a healthy dose of perspective, we'll look at ways to manage stress more effectively, build resilience, set boundaries, and develop habits that help us perform at our best without burning out.
    We'll also explore how we can better support our colleagues and create team cultures where well-being is treated as seriously as productivity.

    By the end of the session, you'll leave with practical ideas and simple strategies to help protect your own mental health, support those around you, and thrive in an industry that never stands still.

    ACP (Flamenco)
    Mon 10:30 am - 11:30 am
    • English
    • Introduction

  • The Visual Workout: 7 Practical Exercises for Stronger Reports and Clearer Data Visualisation

    Great reports are built like great workout routines: you need a clear goal, the right technique, consistent structure, and the discipline to leave out anything that only looks impressive but does not create results. For data visualisation, the same principle applies: without a sound plan, adding more visuals, filters, and interactions will not make a weak report stronger; it will only make it sweat more.

    In this hands-on session, we will go through a practical Visual Workout: seven exercises designed to strengthen your analytical reports. Each exercise focuses on one concrete design capability, supported by live demos, templates, and before-and-after examples.

    We will start with the “core strength” of effective reporting: purpose, audience, and decision context. From there, we will use a report design blueprint, sketching techniques, and mockups to design better analytical experiences before touching the final tool. Then we will work through practical redesign exercises: choosing better visuals, reducing cognitive load, improving layout alignment, using color with discipline, and turning analytical findings into clear, actionable visual communication.

    This session is designed for data professionals who want immediately applicable methods, not abstract design philosophy. Come prepared for report push-ups, chart-type squats, and maybe a few burpees for unnecessary pie charts.

    Key Takeaways

    * A repeatable 7-step workflow for improving analytical reports
    * How to use templates such as a report design blueprint and mockups in real projects
    * How to select visuals based on analytical intent, not habit
    * How to reduce cognitive load and make reports easier to scan and understand
    * How to turn analytical findings into clear, actionable visual communication

    Foxtrott
    Mon 10:30 am - 11:30 am
    • English
    • Intermediate

  • Data Warehousing for the AI Era: Deep Dive into High-Performance Analytics and GPU-acceleration

    AI is raising the bar for analytics performance, scale, and interactivity.
    Join us for an inside look at the innovations powering Fabric Data Warehouse and how we’re building for the AI era. See how GPU-accelerated query processing is redefining analytics performance and enabling faster insights at higher concurrency and unlocking new possibilities for large-scale workloads.

    We’ll also go under the hood to explore the architecture, query optimization innovations, intelligent resource management, monitoring capabilities, and the latest performance enhancements across the platform.

    Whether you’re optimizing existing workloads or preparing for the next generation of AI-powered analytics, you’ll leave with a deeper understanding of what’s new in Fabric Data Warehouse and where data warehousing is headed next.

    Ballerina
    Mon 10:30 am - 11:30 am
    • English
    • Advanced

  • Moving day in OneLake: Copy, mirror or shortcut?

    Not so long ago, getting data into an analytical platform meant one thing - you packed it up, shipped it over and hoped nothing broke on the way. Microsoft Fabric has turned that single moving truck into an entire logistics company: Copy jobs, pipelines, Dataflows Gen2, notebooks, Mirroring, Shortcuts… and Eventstreams waving from the express lane. Plenty of choice - and plenty of ways to pick the wrong one.

    In this session, we'll skip the feature tour and go scenario by scenario: full and incremental batch loads, change data capture, near real-time replication and the "don't move it at all" zero-copy approach. For each one, we'll show which tools fit, where they fall short and what they really cost - in capacity units, not just in effort. We'll focus on side-by-side comparisons, check which surprises might get you on the CU side, and all the small things the documentation tends to keep quiet about.

    Ultimately, this session should leave you with a decision framework for various scenarios, each one leveraging the best possible Fabric loading choice.

    Concerto
    Mon 10:30 am - 11:30 am
    • English
    • Intermediate

  • Rayfin, Rides and Writeback: Fabric Apps That Aren't Reports

    Every new Fabric feature gets the same first demo: a prettier report. Rayfin and Fabric Apps (preview) can do far more. Define a data model in TypeScript and you get a database, GraphQL API, Entra SSO, row-level security and hosting, deployed to a workspace with one command.

    So what do you build when your data platform can ship software? Rob shows apps people actually use: writeback tools that fix data rather than admire it, an admin console calling the Fabric REST APIs through server-side functions, and a cycling and fitness app that pulls rides from Strava, lands them in OneLake and turns training data into something you act on, not just look at.

    Along the way: schema changes that don't eat production, dev-to-prod promotion, keeping secrets out of the frontend, and an honest view of where the preview still creaks.

    You'll leave with patterns, a repo, and a better answer than "another report".

    Symphonia
    Mon 10:30 am - 11:30 am
    • English
    • Intermediate

  • Flying High on Data Accuracy: Lessons from Aviation for Trustworthy AI

    In aviation, data accuracy is critical. From flight operations and maintenance to safety and planning, even small data errors can have significant consequences. As organizations increasingly use AI to make predictions, generate insights, and support decisions, the same principle applies: AI is only as reliable as the data behind it.

    This session explores lessons from aviation data operations and how they can be applied to building reliable, AI-ready data pipelines. We will look at how automated validation, monitoring, and data quality checks can help identify issues before they reach downstream analytics and AI systems.

    Key topics include:

    * Designing automated validation for data completeness, integrity, consistency, and timeliness
    * Using schema validation, anomaly detection, and business rules to strengthen AI-ready data
    * Monitoring data pipelines continuously to detect issues before they impact AI outputs
    * Understanding how poor-quality or incomplete data can affect AI-generated insights and decisions
    * Lessons learned from aviation data operations, including practical challenges and pitfalls
    * Scaling automated data quality and monitoring across modern data platforms

    Attendees will leave with practical approaches for building more reliable data foundations for AI. The goal is not simply to test data, but to create a continuous approach to data reliability that increases confidence in both analytics and AI-powered solutions.

    Because when the data matters, the quality of the decision depends on it.

    Menuett
    Mon 10:30 am - 11:30 am
    • English
    • Intermediate

  • Data Storytelling vs. Data Truth: When Narrative and Integrity Collide

    Data tells stories. But stories have heroes, villains, and a point — and data, on its own, has none of those. Someone has to shape it into stories.

    In this session, we dig into the tension that lives at the heart of every dashboard, report, and presentation: the pull between crafting a compelling narrative and staying rigorously honest with the data. We'll look at how well-intentioned storytelling can quietly distort conclusions, how context gets lost in the name of clarity, and how the pressure to communicate "a clear message" can nudge even careful analysts toward choices they'd rather not defend.

    We'll explore:

    - Where the line sits between simplification and misrepresentation
    - How design, framing, and sequencing shape what people believe
    - The organisational pressures that make honesty harder than it sounds
    - Practical principles for telling true stories, compellingly

    Whether you're building reports, presenting to leadership, or trying to hold the line on something that doesn't feel quite right - this session is for you. Come with your examples, your dilemmas, and your own experience of where the line sits. We will talk about the everyday tension between being understood and being accurate.

    ACP (Flamenco)
    Mon 11:45 am - 12:45 pm
    • English
    • Intermediate

  • How to Leverage AI for LinkedIn Visibility as a Data Professional

    Data professionals face a paradox. They're skilled in what they do: building models, designing schemas, solving complex analytical problems. But on LinkedIn, they're invisible.
    Most data professionals don't post regularly, or when they do, their content gets lost in the feed. And when they try to use AI to create more content faster, they hit a new problem: most AI-generated content sounds generic, impersonal, and (ironically) exactly like everyone else's.
    Meanwhile, many of these professionals run side projects. Some freelance. Some do trainings. Some do consultancy. Some combine a full-time job with a side-project. But their side projects can't grow because the right people don't know they exist. And when people do find them, generic AI content doesn't build the trust they need.
    The real issue isn't a lack of skill or expertise. It's a lack of a visibility system that works with their time constraints and doesn't sacrifice their voice in the process.

    What You'll Learn:

    In this session, I'll walk through the exact workflow I used to grow to 7,000+ LinkedIn followers and fill 5 successful Power BI PL-300 bootcamps with 130+ students, all while working full-time as Head of BI and raising two young children. The same system that helps data professionals turn their technical work into content that brings in consulting clients and fills their training programs.

    You'll learn:
    → Why most AI-generated content fails for technical professionals, and what actually makes it sound like AI
    → How to use Claude/ChatGPT and Obsidian to build a content system that works in 30-60 minutes a day
    → A repeatable workflow that turns your daily technical work into weekly LinkedIn posts without sounding generic
    → The three key ingredients that make AI-assisted content actually sound like you (instead of like everyone else)
    → How to position yourself on LinkedIn so the right opportunities find you, whether that's freelance clients or students for your training programs

    This isn't about personal branding or becoming an influencer. The focus is to be found by the people who need your expertise.

    Who Should Attend;

    This session is for Microsoft Data Platform professionals. Whether you're a developer, analyst, engineer, consultant, or architect, who run a side project (freelance work, training programs or consulting) and want to grow it.
    You have valuable expertise. You just need the visibility system to match it.

    Foxtrott
    Mon 11:45 am - 12:45 pm
    • English
    • Introduction

  • OneLake in Microsoft Fabric and what you should know about it

    OneLake is the central data access layer in Microsoft Fabric, but it is more than just that. Over the past two years, a lot of changes and additions have been added to OneLake to make it a more complete and manageable center of your Fabric Implementation and a core piece in Microsoft's IQ strategy.

    During the session we will look at the options you have in OneLake to expose, discover, manage and govern data, from shortcuts via Lifecycle management to OneLake Security.

    Ballerina
    Mon 11:45 am - 12:45 pm
    • English
    • Intermediate

  • Soft skills for hard problems: Get an edge in data leadership

    You work with high-stakes projects and are dependent on other people. You can optimize your query, but you can’t optimize your team. The hardest problems aren’t in the code. They’re in communication, in misalignment and tensions that drain energy and impact the measurable results.

    In this session you’ll learn how to create alignment in cross-functional teams and use feedback that actually works. We’ll dive into a hands-on exercise that helps make collaboration smoother and more effective.

    After this session, you will:

    * Master a proven feedback method that improves collaboration and reduces friction.
    * Know how to create alignment in complex teams to deliver with less stress.

    Join this session to learn how to optimize the most critical component in your everyday work - your people.

    Concerto
    Mon 11:45 am - 12:45 pm
    • English
    • Introduction

  • Fabric IQ and the Ontology - A no-code approach to governing your data

    Every organisation has the same problem. Business terms are defined differently across teams, semantic models duplicate the same definitions, and your AI agents have no clue what the data actually means. The result is conflicting reports, governance headaches, and hours spent on things that should have been solved from the start.

    Fabric IQ is set to change this. With the Ontology item in Microsoft Fabric, the business gets a no-code approach to define entities, relationships, and rules in one single place. Once defined, these definitions are automatically picked up by AI agents, semantic models, and services across Fabric - and beyond, into AI Foundry and Work IQ.

    In this session, you will see how to set up your first Ontology from scratch or based on existing semantic models, link it to your data entities in Fabric - including time-series, bulk loaded, and geospatial data - and watch how AI agents use these definitions without extra configuration. No marketing fluff. Hands-on demos and practical guidance you can use the day you get back to the office.

    Symphonia
    Mon 11:45 am - 12:45 pm
    • English
    • Introduction

  • Which Point in Time Do You Mean? - The Challenge of Designing Historical Reporting End-to-End

    Most analytical projects put considerable effort into preserving history. There are plenty of established patterns and architectural blueprints for storing historical changes in raw data. Yet, much less thought is often spent on how historical perspectives should ultimately be exposed to business users.

    "We want to support every possible historical question" often seems to be the only requirement. This works reasonably well in core data warehouse layers and relational dimensional models. However, when teams try to expose historical data through a general-purpose Power BI semantic model, they frequently discover that historical data is far more difficult to consume than it is to store.

    A seemingly simple business question can produce multiple valid answers depending on which historical perspective is applied. Deciding which of these perspectives should be supported and exposed to end users is often the real challenge.

    This session explores the foundations of temporal data and historical reporting, different categories of temporal business questions, and their implications for data modeling, architecture, and analytics. Particular attention is given to the gap between what can be represented in a data warehouse and what can realistically be delivered through Power BI semantic models and reporting solutions.

    Using real-world examples, we will discuss common implementation approaches, their trade-offs, and the pitfalls that arise when historical perspectives are not explicitly defined. The session advocates considering time-related reporting requirements from the very beginning of a project instead of attempting to build a universal model capable of answering every possible temporal question.

    Menuett
    Mon 11:45 am - 12:45 pm
    • English
    • Intermediate

  • Scaling Machine Learning with Microsoft Fabric: From Predictions to Business Insights

    How do you operationalize machine learning at scale and make predictions accessible to business users?

    In this session, we will explore an end-to-end architecture for large-scale machine learning on Microsoft Fabric. We will show how distributed model training, prediction serving, Power BI reporting, and Fabric Data Agents can be combined into a seamless analytics experience.

    ACP (Flamenco)
    Mon 1:45 pm - 2:45 pm
    • English
    • Intermediate

  • From Zero to Fabric Apps: Automated Transformation and Deployment with Rayfin

    Fabric is the new holistic data platform in your company – and you are facing countless existing reports, evaluations, and dashboards in various notebooks and repositories that now need to be migrated and connected. Sooner rather than later.

    In this hands-on session, we do exactly that: we transform contents of existing repositories into a ready-to-use Microsoft Fabric App – from scratch, on stage. We start by examining different types of input projects to transform their existing code and data with the help of off-the-shelf frontier models. With Rayfin's open source SDK and CLI we create the project scaffold, derive the SQL schema, and deploy the result live to Azure as a Fabric App with a single command.

    That sounds simple, but what actually happens when the underlying schema in Fabric changes, and how can you ensure a clean, repeatable re-deployment with Rayfin?

    In summary, this session shows how to structure, transform, and deploy existing code repositories into a Fabric App in an fully automated way and why "Schema-as-Code" is important for Fabric SQL databases.

    Foxtrott
    Mon 1:45 pm - 2:45 pm
    • English
    • Advanced

  • Govern Once, Discover Everywhere: Data Governance with OneLake Catalog

    Data governance is the foundation of trusted analytics and AI. In this session, discover how Microsoft Fabric and OneLake Catalog help organizations find, understand, secure, and govern data at scale. Learn how to leverage metadata, lineage, domains, data products, and governance controls to improve compliance, trust, and self-service adoption. Through practical demonstrations and real-world scenarios, you'll leave with actionable guidance for modern data governance.

    Ballerina
    Mon 1:45 pm - 2:45 pm
    • English
    • Intermediate

  • Highlights and Hidden Gems in SQL Server 2025

    With so much emphasis on cloud data platforms and AI these days, SQL people can feel left behind by all the marketing hype. SQL Server 2025 was officially released in November of 2025, though, and contains a ton of improvements that will make our SQL Server environments a bit faster, better, and more secure. There are even more improvements tucked into the release that never made a marketing blog or press release that you'll likely be learning about for the first time in this session!

    Join this session to learn about what makes your high availability a little more available, your performance a bit more performant, and your database more developer and app-friendly. Come spend an hour with SQL people talking SQL Server 2025 – the good, the "not quite ready for prime time", and the hidden awesomeness.

    Concerto
    Mon 1:45 pm - 2:45 pm
    • English
    • Intermediate

  • Finance Reporting in Power BI: One Model, Three Visual Stacks Compared

    Finance reporting always asks the same questions: AC vs PY, PL and FC, MTD/YTD/FY, Local vs Company Currency, current rate vs budget rate — on real data volumes. This 60-minute session designs a lean Power BI model that handles all of it, then walks through the same dashboard implemented three ways: Core Visuals with SVG, Deneb, and a paid custom visual. Compare IBCS fit, performance, cost, maintainability, and self-service in the age of AI — honest trade-offs.

    Symphonia
    Mon 1:45 pm - 2:45 pm
    • German
    • Intermediate

  • The Power BI Report Was Fine. Nobody Used It.

    You built the report. It had everything that was asked for. And then nothing happened. No follow-up questions, no decisions made, just silence. That feeling is more common than most people admit, and most of the time the real problem started long before you opened Power BI.
    In this session we look at what actually goes wrong before the build. We go through the questions that most people skip: who is the audience, what decisions should this report support, and how will you know if it works? Answering these before you start is not a luxury, it changes everything about what you end up delivering.
    You will walk away with a practical way of working that closes the gap between a report that looks fine and one that people actually come back to.

    Menuett
    Mon 1:45 pm - 2:45 pm
    • English
    • Introduction

  • From Data to Decisions: UX, AI & Mockups for Better Power BI Dashboards

    What if we design the dashboard before opening Power BI—and use AI to help us do it?

    In this session we’ll explore how Design Thinking, UX principles, and AI can transform the way we approach Power BI dashboard design.

    Instead of starting with charts, KPIs, and visuals, we’ll start with the most important element: the person using the data. We’ll move from understanding user needs and business questions to defining information hierarchy, sketching ideas, and creating dashboard mockups.

    Along the way, we’ll use AI to accelerate the mockup development process, turning ideas and requirements into visual concepts that can be quickly explored and iterated. The goal is not to let AI design the dashboard for us, but to use it as a creative partner while keeping UX, user needs, and decision-making at the center.

    You’ll discover a practical approach to designing Power BI reports that are not only informative, but also intuitive, focused, and actionable.

    Because a great dashboard isn't about showing more data... It’s about creating a better experience for the people making decisions with it.

    ACP (Flamenco)
    Mon 3:00 pm - 4:00 pm
    • English
    • Intermediate

  • Mastering Statistics in Microsoft SQL Server

    Statistics are one of the most powerful — and most misunderstood — components of the SQL Server query optimizer. They drive cardinality estimation, influence join strategies, shape memory grants, and ultimately determine whether a query runs in milliseconds or minutes. When they’re fresh and accurate, statistics make SQL Server look brilliant. When they’re stale, incomplete, or misleading, they can bring even the best‑designed systems to their knees.
    This session takes you deep into the world of SQL Server statistics: what they are, how they work, and why they matter. We’ll explore histogram structures, density vectors, cardinality estimation models, and how SQL Server uses statistics to choose execution plans. You’ll learn the difference between auto‑created and user‑created statistics, when filtered statistics shine, and how ascending keys, skewed data, and parameter sensitivity can sabotage even the most carefully indexed workloads.

    Foxtrott
    Mon 3:00 pm - 4:00 pm
    • English
    • Advanced

  • Not Everything Needs Direct Lake: Practical Storage Mode Decisions

    Is Direct Lake the answer to everything? With Microsoft Fabric, many see Direct Lake as the default choice for semantic models, but the reality is far more nuanced. Choosing between Import mode, Direct Lake over OneLake, and Direct Lake over the SQL Endpoint depends on far more than just performance.

    In this session, we take a practical look at when each storage mode makes the most sense. We compare capacity impact, engine behavior, and the difference between on-demand loading versus loading the full model into memory.

    We also cover semantic modeling implications for model authors, Direct Lake fallback scenarios, and the performance impact of poorly designed Delta tables and partitioning strategies.

    Learn how to make the right storage mode decision instead of simply following the hype around Direct Lake.

    Ballerina
    Mon 3:00 pm - 4:00 pm
    • English
    • Advanced

  • Power BI Performance: Diagnose, Treat, Optimise

    A slow Power BI report is only a symptom. Before trying random optimisations, you need to identify what is actually causing the problem.

    Is the issue hidden in the data model, the DAX calculations, the report design, Power Query, or the data source? Applying the wrong treatment may have little effect and can sometimes make the solution even more complicated.

    In this session, we will follow a structured performance-tuning process: diagnose the symptoms, identify the bottleneck, apply the right treatment, and measure the results. We will look at common performance problems in semantic models, DAX measures, relationships, visuals, and data preparation. We will also explore the tools that can help investigate them, including Performance Analyzer, DAX Studio, and Power Query diagnostics.

    By the end of the session, you will know how to approach slow Power BI solutions systematically, choose the right optimisation technique, and build reports that remain fast, efficient, and maintainable.

    Concerto
    Mon 3:00 pm - 4:00 pm
    • English
    • Intermediate

  • Your Agent Is Doing ETL (and You're Paying for It): AI Architecture with Fabric and Microsoft IQ

    All year, I've watched the same pattern play out. AI teams ship fast: Foundry over SharePoint, agents live in weeks. The extraction, transformation and data quality fixes happen inside the model, paid for in tokens. And now the bills are arriving. Meanwhile, data teams who've spent years asking for platform investment say "foundations first", and lose the room.

    I've been on the losing side of that conversation. This session is how I learned to win it.

    Starting from the business value you're chasing, we'll build an enterprise architecture that separates knowledge from data: strategy pillars underneath, a consumption layer on top, and Microsoft IQ pulling it together.

    I'll share my AI ready data design model: three principles, scored against value, feasibility and cost, so teams decide with numbers rather than vibes.

    The next AI build will land on your desk whether the data is ready or not. Let's make sure data people are in the room, and that we're part of shipping better, faster.

    Symphonia
    Mon 3:00 pm - 4:00 pm
    • English
    • Intermediate

  • Semantic Models in Microsoft Fabric: Building the Foundation for the Enterprise Semantic Layer & AI

    For years, we've built semantic models primarily to serve Power BI reports. That role is changing.

    As organizations adopt Microsoft Fabric and AI-powered analytics, semantic models are becoming part of something much bigger: an enterprise semantic layer that defines business terminology, relationships, measures, KPIs, and context once and makes that knowledge reusable across analytics and AI.

    In this session, we'll explore what that shift means in practice.

    We'll look at how semantic models fit into a modern Fabric architecture, why simply creating a single giant enterprise model is rarely the answer, and how multiple domain models can work together within a governed semantic layer.

    We'll also explore why this becomes increasingly important for AI experiences such as Copilot and Fabric IQ. Giving an AI access to data isn't enough - it also needs the business context to understand what the data means.

    You'll leave with a practical architectural perspective on how to move beyond report-centric semantic models and start designing a reusable semantic foundation for both enterprise analytics and AI.

    Menuett
    Mon 3:00 pm - 4:00 pm
    • English
    • Introduction

  • From Individual Contributor to Data Leader: The Skills No One Teaches


    Moving from engineer or analyst to data leader isn’t just a promotion, it’s a complete shift in mindset. As a female leader, completing an MBA, and leading modern data teams, I realised something uncomfortable: no one actually teaches you how to make this transition.

    In this session, I’ll share real lessons from moving out of delivery and into leadership, influencing without authority, handling conflict, setting priorities, and leading mixed-skill teams in organisations where data is no longer a support function, but the core of the business.

    Data teams are different. They can’t afford to be reactive or purely technical anymore. They must be agile, outcome-driven, and business-facing, while still protecting quality, wellbeing, and trust.

    This is an honest, experience led session about what worked, what didn’t, and what I wish I’d known earlier, especially navigating leadership as a woman in highly technical environments.

    No theory. No leadership buzzwords. Just practical insight from the field.

    ACP (Flamenco)
    Mon 4:15 pm - 5:15 pm
    • English
    • Introduction

  • From Convenience to Control: Breaking Free from Big Tech Data Platforms

    Many modern data platform infrastructures - like those you can build in Microsoft Azure or directly use like Microsoft Fabric - offer convenience, require less technical know-how, and provide direct integrations into other services. At the same time, they also create large dependencies on their platforms that are deeply rooted and difficult to break.

    However, with the current geopolitical climate and tensions between the US and Europe, many European organisations are questioning what it really means to rely heavily on US-based technology and are looking for ways to break away from those dependencies and move towards more digitally sovereign solutions.

    In this session we are focusing on a practical path forward: how to migrate from Microsoft Azure and Fabric towards a sovereign data platform that is fully in control of your organisation and at the same time complies with all relevant European legislation.

    We will map existing Microsoft components to open-source or European alternatives, design an architecture that is open, modular, controllable, and vendor-independent, and of course, discuss the trade-offs involved in moving away from Big Tech data platforms.

    Instead of a theoretical discussion, this talk dives into real-world migration strategies and lessons learned from helping organisations move towards a data platform infrastructure without dependencies and fully in their own control.

    Foxtrott
    Mon 4:15 pm - 5:15 pm
    • English
    • Intermediate

  • Scaling Clustered Column Store Indexes

    Clustered Column Store Indexes are a great tool when used correctly. This session will explain on how to plan, configure, and operate Clustered Columstore indexes to handle trillions of rows. This is done with a real world example that is in production. Avoiding mistakes in the beginning will save you lots of data wrangling over time. Come and learn how to partition, select the right datatypes, and insert the data into a Clustered Column Store Index to achieve optimal performance results.

    Ballerina
    Mon 4:15 pm - 5:15 pm
    • English
    • Intermediate

  • Who is burning your capacity ...and what can you do against it

    Ever wondered which workload consumes all your capacity? Ever wished you could protect your capacity from over-usage? - Then this session is for you!

    First we will cover the basics like Capacity Units (the currency of Fabric), background and interactive processes, bursting, smoothing and throtteling. Then we will take a look on different tools to monitor your capacity and how to protect your most important workloads.

    After this session you will
    * have a solid understanding about capacity metrics,
    * know how to identify your most expensive workloads
    (* and ultimatley know whom to blame for it ;-))

    If you want to keep your users happy by providing always enough capacity with out driving your CFO crazy - this session is for you.

    Concerto
    Mon 4:15 pm - 5:15 pm
    • English
    • Introduction

  • Data Viz Placeholder

    Symphonia
    Mon 4:15 pm - 5:15 pm

  • Code, Commit, Deploy: Automating Fabric with Terraform and Git

    We’ve all been there, setting up multiple workspaces, clicking through the same settings, and wondering if there is a better way? Microsoft Fabric is powerful and as the platform evolves, so does the need for automation. Knowing where to start with Infrastructure as Code, Git integration, and deployment practices can still be a bit of a puzzle.

    In this session, we’ll take a practical look at how to bring automation into your Fabric environment, so you can spend less time clicking and more time focusing on your data.

    We’ll start with an intro to Terraform and how it works with Microsoft Fabric. We'll walk through what you can (and should) manage with Terraform, and what’s better handled inside Fabric itself. We'll then continue to dive into how Git integration works and what capabilities it provides, as well as how it supports a more versioned and collaborative way of working. Along the way, we’ll highlight common patterns, share real-world tips, and highlight some important details to make things work smoothly.

    Throughout the session we will also be walking through a demo to highlight both parts of the implementation; provisioning workspaces and capacities with Terraform, and deploying Fabric items using Git integration, so you can see how everything fits together in practice.

    Whether you’re building full pipelines or just want to simplify your setup, you’ll leave with a clearer path toward smoother deployments!

    Menuett
    Mon 4:15 pm - 5:15 pm
    • English
    • Intermediate
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