Devon and Cornwall Microsoft Power BI User Group

Profitability is a key metric; any profits can be distributed back to shareholders (owners) either directly or indirectly. A profit and loss (P&L) statement answers high level questions - such as “what was net profit last year?” - and summarises key revenue (i.e., product revenue) and expense (i.e., Research & Development) items. Unlike static reports, a P&L semantic model contains the detail; this allows end-users to ask questions such as “what was R&D spending broken down by a particular research project, fiscal period, or legal entity?.” A semantic model also allows end-users to consume information using Copilot prompts, Power BI reports, or Pivot Tables and formulas in Excel.

In this session, we will go through:
- Why you should build an income statement semantic model.
- How to use an accelerator to speed up development.
- The key questions you need to ask stakeholders.
- The challenges in building a P&L income statement.

Chris Barber is a chartered accountant (ACMA, CGMA) and Microsoft MVP. He is the author of income statement semantic models, advises Avanade/Accenture clients on building solutions using the Microsoft BI stack, and runs StarSchema.co.uk.

Navigating the DAX Dimension: Your Guide to DAX Query View

Fasten your seatbelts and prepare for takeoff as we embark on a voyage through the DAX Query View in Power BI Desktop. In this presentation, we’ll explore the uncharted territories of Power BI with the help of our Copilot, who’s more than just an assistant – it’s the Goose to your Maverick in the Top Gun of data analytics.
As we soar through the skies of ‘SUMX()’ and dodge the turbulence of ‘RELATEDTABLE()’, our Copilot will ensure we don’t crash into the dreaded ‘Syntax Error’ mountains. We’ll navigate through the clouds of complex calculations with ease, thanks to our Copilot’s knack for translating ‘DAX-ese’ into plain English. Watch as we perform daring maneuvers, like seamlessly integrating ‘CALCULATE()’ functions with a flick of the wrist and rescuing lost measures from the Bermuda Triangle of ‘Bad References’.
By the end of this high-flying adventure, you’ll not only have learned how DAX Query View can ease your relationship with DAX but also discovered the joy of having a Copilot who can crack jokes while crunching numbers. So, let’s chart a course for fun and function, and may our Copilot’s humor be as ‘calculated’ as our formulas!

This session is designed to introduce participants to the core features of Databricks.

You'll learn to navigate Databricks' interface: manage clusters, SQL editor and use notebooks to write and execute code.

By the end, you’ll gain the skills to manage clusters, automate workflows, and leverage Databricks for powerful data-driven insights.

The session requires no pre-requisite knowledge of Databricks.

Join me for a practical dive into Databricks' capabilities and features!

Blog:
Vitalija thrives on turning complex data into actionable insights.

For her PhD she spent years in a lab collecting data on fish, and gained a deep understanding on science-grade quantitative analytics.

Today she works as a consultant - data engineer primarily solving business problems using Azure Databricks.

She loves to talk about data and exchange best practices.

When not at work she loves champagne.

Do you want to enhance the performance of your dashboard? Experience shows that most performance issues in Power BI can be addressed with a few simple adjustments to the data model.

Therefore, this session will address the following questions:
- What constitutes a strong foundation for a data model?
- What are the advantages and disadvantages of different data models?
- How can you manipulate data to generate the right insights?

A robust data model can resolve many issues effortlessly, including:
- Even with limited expertise, you can boost performance with a few tips, resulting in faster loading times for your reports.
- Utilizing the appropriate data model makes it easier to craft DAX formulas, reducing complexity in the process.

By the end of this session, you'll have a clear understanding of what factors to consider. You can then apply this knowledge directly to your daily tasks.

Peter is a BI consultant, speaker, and founder of Dutch BI Geek. He helps organizations turn bulky data models into fast, efficient ones – with smart structures, clean relationships, and DAX that actually performs.

His specialty: boosting performance from the ground up. No quick fixes, just technically sound, scalable models. Peter explains complex concepts in a clear – and sometimes surprisingly fun – way, from CALCULATE to context transitions and compression.

Geek by design. Because performance isn’t optional.