(Livestream Replay) Power BI Automation With Semantic Link - Sandeep Pawar

DESCRIPTION 📄

Semantic Link in Microsoft Fabric offers a new way to access the data and semantic information contained in a semantic model. This allows data scientists, data engineers and data analysts to preserve and re-use the business and domain knowledge in creating enterprise solutions.

In this session, Sandeep will give you an overview of Semantic Link and provide practical use cases to use Semantic Link in your development workflow to automate common Power BI tasks, optimize the semantic models and also monitor/manage the tenant. He will also show Semantic Link Labs, an open-source Python library with hundreds of useful utilities.

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Sandeep is a Sr Power BI Architect at Hitachi Solutions America where he helps organizations build enterprise analytics solutions using Microsoft data stack. He blogs about Data Engineering, Data Science and Power BI at fabric.guru

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(Livestream Replay) Power BI Meets UX Design: Accessible Insights - Elena Drakulevska

DESCRIPTION 📄

Imagine creating an amazing report—rich in insights and visuals—only to discover your audience can't use it or struggles to grasp its depth. In "Accessible Insights" we'll dive into inclusive UX design principles, revealing the strategic use of icons, text, and visual cues within Power BI.

Stepping into the shoes of users with varying abilities, we'll emphasize the crucial role of empathetic design and uncover the hidden, built-in accessible capabilities of Power BI.

Join this talk to learn how to create reports that transcend barriers and speak universally to diverse audiences. After all, accessibility is not just a buzzword—it's a necessity.

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Elena Drakul(evska) is a BI Consultant with a Master’s in Telecommunications Engineering from Politecnico di Milano and she’s currently based in Vienna, Austria. With a couple of years of experience across various industries, she brings a unique perspective to the intersection of tech, business, and design.

Passionate about both Power BI and UX Design, she finds immense joy in blending the two to create impactful data visualizations. As a fresh speaker at numerous data conferences and the author of her blog Moonstory, she shares her insights and expertise with a global audience.

When she’s not working magic with data, Elena can be found exploring the world, picking up new languages, doing yoga, and immersing herself in great books.

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Not All Query Folding is Created Equal...Performance Tuning PQ

Video by: Reid Havens

Everyone knows rule number one for Power Query performance is to ensure your query folds as much as possible. What do you do after rule number one? There is more to performance than just folding, and there are multiple approaches that can fold.

In this video, we deep dive into multiple queries with folding that all have different performance characteristics. We'll examine dates and lists and how M generates SQL when folding.

Tune in to see how you can check the efficiency of different folded queries!

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He slices! He dices! When it comes to Power BI, Greg Baldini does it all, and he is here to show you how to, too!

Co-founder of Argus PBI, Greg has a decade of experience with DAX, Tabular, and the Power BI family of tools. His career has been spent in solving hard problems for clients and seeking deep understanding of the fundamentals of data analysis.

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Medallion Architectures...Do They Actually Work??? - Simon Whiteley

DESCRIPTION 📄

We’re sold, we’re all about building lake-based data platforms these days – but whether you’re all about the Fabric Lakehouse or Warehouse, whether you’re into custom lakes or OneLake all the way, there are constant arguments about how things should be structured. What if you’ve gone medallion but the zones don't quite fit what they were trying to achieve, and no one in the company understands what "silver" vs. "gold" actually means?

Is the Medallion Architecture right for most businesses - and how should you interpret the advice? What are the different stages of data curation and how do they work in reality? How should we think about schema evolution, data cleansing, record validation, and traditional data modeling techniques, layering them on top of our medallion zones so we truly understand what happens where.

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Simon is a Databricks Beacon, Microsoft MVP and owner of Advancing Analytics. He’s been building and designing lakehouses before they were called lakehouses, and spends most of his time championing data engineering and ranting about Spark on Youtube. When not tinkering with tech, you’ll find Simon wandering the streets of London, always hunting for interesting things to eat, drink and do!

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