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.

When: Thursday 20th February 2025 Time: arrive for 5:45pm with talks starting from 6pm start prompt.

Location: BJSS, 90 Victoria St, Redcliffe, BS1 6DP

Complimentary drinks & pizza provided by our hosts BJSS

Social drinks afterwards will be at Ye Shakespeare (50m away) for those interested.

This #MSFABRICBRISTOL will feature Chris Barber and Rishi Sapra

Session 1 - P&L Models - Chris Barber 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

About Chris Chris Barber is a chartered accountant (ACMA, CGMA), 4 times Microsoft MVP, author of Income Statement Semantic Models, runs StarSchema.co.uk, and has popular YouTube videos (over 100k views) and courses (over 1k participants) on the topic of Profit and Loss (P&L) using Power BI.

Session 2 - Financial Reporting in PBI - Rishi Sapra This session will explore how to transform a traditional Excel-based credit rating model for countries into a modern, interactive, and scalable solution using Power BI and Microsoft Fabric. Participants will discover innovative techniques to enhance financial modelling and storytelling by leveraging advanced analytics and integration capabilities.

Hear from Power Platform in Finance specialist and Microsoft MVP, Rishi Sapra, as we delve into the following areas:

• Replicating Complex Rating Logic: Translating intricate credit rating formulas and methodologies from Excel into DAX to ensure consistency and accuracy.
• Interactive Insights: Using slicers, bookmarks, and contextual visualizations in Power BI to enable dynamic comparisons and highlight key drivers of credit ratings.
• Streamlined Reporting: Designing intuitive and user-friendly reports that empower stakeholders to explore insights interactively.
• Scalability with Microsoft Fabric: Harnessing the Medallion Lakehouse architecture to enable seamless data integration, metadata management, and collaboration at an enterprise level.

This session is particularly beneficial for finance professionals and analysts who are seeking to modernize their financial or operational models. Attendees will leave with practical strategies to maintain model accuracy, enhance interactivity, and scale their solutions to meet the evolving demands of modern analytics.

About Rishi Rishi has a unique blend of technical and commercial skills - he is a 5x Microsoft Most Valuable Professional (MVP), a Chartered Accountant, a Microsoft Certified Trainer (MCT) and an Executive MBA (Hons) holder with a first class degree from the London School of Economics.

He currently works as a Data & AI Strategic Project lead at Avanade - a Joint Venture between Accenture and Microsoft which been awarded Microsoft Partner of the Year 18 times! In this role he focuses on Microsoft Fabric Go To Market (GTM) offerings including those around Security & Governance, Industry/Functional accelerators and Azure/BI migration.

Prior to joining Altius in 2017 (Which was acquired by Avanade in 2020), he spent 12 years in the Big 4 /Financial Services (Deloitte, HSBC, Barclays, KPMG) and has a strong background in Business modelling and process improvement.

He is actively involved in the Fabric Community in London/globally and has presented at Meetup groups and several large-scale conferences. His passion is in helping organisations achieve the holy grail of Self-Service BI and helping individuals learn the necessary skills to succeed. Under his community Learn Data Insights (www.learndatainsights.com), he runs Microsoft Fabric Training (www.msfabrictraining.com) and Power Platform Finance (www.powerplatformfinance.com) with e-learning courses and quizzes for Analytics and Finance professionals.

We all look forward to seeing you there!!

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:

1. Why you should build an income statement semantic model.
2. How to use an accelerator to speed up development.
3. The key questions you need to ask stakeholders.
4. The challenges in building a P&L income statement.

Bio 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.

Chris's book "Income Statement Semantic Models: Building Enterprise-Grade Income Statement Models with Power BI" will be published on 28th August. You can pre-order it on https://amzn.eu/d/6uxJfu2

Details

PBIMCR September 2024 session

When: Thursday 26th September 2024 Time: arrive for 5:30pm onwards with talks starting from 6pm start prompt Location: Slalom - Bloc \| 17 Marble St \| 12th Floor \| Manchester \| M2 3AW \| Session will not be streamed over MS Teams

September's PBIMCR will feature

Session 1 Title: Profit & Loss Semantic Models in Power BI

Abstract: 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.

Speaker 2: David Mitchell (Microsoft) Fabricating Your Move: A Tailored Path from Power BI Premium to Fabric

As Power BI evolves into Microsoft Fabric, transitioning from Premium to Fabric capacities unlocks new possibilities. In this session, discover a streamlined, automated solution using Semantic Link Labs that ensures a smooth migration, enhancing your analytics capabilities. We’ll explore key features, benefits, and demonstrate the process in action, equipping you with the tools to effortlessly embrace Fabric. Join us to learn how to future-proof your analytics environment with minimal effort and maximum efficiency.

David is a Senior Cloud Solution Architect at Microsoft, specializing in Data & AI, mainly focusing on the following areas: • Microsoft Fabric • Power BI • Azure DevOps / DataOps • Azure SQL David has worked in data and analytics since 2009 and previously worked at a Microsoft Gold Partner prior to joining Microsoft.

LinkedIn - https://www.linkedin.com/in/davidmitchell85/

This comprehensive guide will teach you how to build an income statement semantic model, also known as the profit and loss (P&L) statement. Author Chris Barber— a business intelligence (BI) consultant, Microsoft MVP, and chartered accountant (ACMA, CGMA)—helps you master everything from designing conceptual models to building semantic models based on these designs. You will learn how to build a re-usable solution based on the trial balance and how to expand upon this to build enterprise-grade solutions. If you want to leverage the Microsoft BI platform to understand profit within your organization, this is the resource you need. What You Will Learn Modeling and the income statement: Learn what modelling the income statement entails, why it is important, and how income statements are constructed Calculating account balances: Learn how to optimally calculate account balances using a Star Schema Producing external income statement semantic models: Learn how to produce external income statement semantic models as they enable income statements to be analyzed from a range of perspectives and can be explored to reveal the underlying accounts and journal entries Producing internal income statement semantic models: Learn how to create multiple income statement layouts and further contextualize financial information by including percentages and non-financial information, and learn about the various security and self-service considerations Who This Book Is For Technical users (solution architects, Microsoft Fabric developers, Power BI developers) who require a comprehensive methodology for income statement semantic models because of the modeling complexities and knowledge needed of the accounting process; and finance (management accountants) who have hit the limits of Excel and have started using Power BI, but are unsure how income statement semantic models are built