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

Just like a shovel, this book is genuinely ground-breaking. It hits you over the head with the proverbial gardening tool, implementing the way forward for financial modelling. Many working in banking and finance create their financial models in Excel and then import them into Power BI for graphical interpretation and further analysis. Not on our watch. We're going to jettison the universal spreadsheet and build the entire model in Power BI.We can't stress how far off the range we're taking the horses. If you are reading this, you are a true pioneer. Some have managed to build the odd financial statement in Power BI, but all three? This is where you can gain a major advantage in the workplace. If you build the calculations for financial statements in Power BI, you can produce statements by product, by customer, by geography... Get the picture? The limitation will be restricted to the granularity of the underlying data and your imagination.This book unearths some of the tricks, measures, logic and tools needed to build the model (there is no need to bury your mistakes). We just can't promise you a rose garden...With the usual jokes in spades, it's just a shame we couldn't get Doug (get it?) to assist.

Have you ever tried to learn to code or to use advanced visualization tools? If so, I am sure you know how daunting it is to learn by yourself. Generally, tools and books follow an encyclopedism approach, i.e., books attempt to teach every feature about a coding language or tool. This implies hundreds, if not thousands of pages simply to tackle a single topic, whether SQL, Python, MS Excel, MS PowerBI, you name it. The journey from zero to hero to become proficient using numerical and visualization tools to take your career to the next level becomes an ordeal that requires years and thousands of pages just to begin putting the pieces of the puzzle together. However, the reality is that you do not need to learn absolutely every available feature to use those tools and deliver a superior project. Rather than teaching you about the forest, I will discuss specific trees. Why? Because once you become familiar and confident nurturing a few trees, growing a forest becomes a simple process of planting new trees. This book provides the fundamental blocks so that you can learn about financial data science and take these tools and start using them tomorrow. The scope of the selected tools will empower you to see a considerable improvement in your financial modeling skills. The book is designed to provide corporate finance professionals the ability to start immediately using advance tools for concrete real-world tasks. Therefore, this book is all about functionalism. It is about providing you with tools that will put you to work and dramatically change the way you analyze data. Once you see the benefits, it will become natural to keep expanding your domain knowledge, leveraging today's endless available educational resources.

Learn how to create your own AI model and consume it in your Power BI reports to gain better insights from your data Key FeaturesLearn how to gain better insights from your data by applying different AI techniques within Power BISave time by creating machine learning models independently and integrating them within your BI reportsUnderstand how to combine Cognitive Services and Azure Machine Learning together with Power BIBook Description The artificial intelligence (AI) capabilities in Power BI enable organizations to quickly and easily gain more intelligent insights from unstructured and structured data. This book will teach you how to make use of the many AI features available today in Power BI to quickly and easily enrich your data and gain better insights into patterns that can be found in your data. You'll begin by understanding the benefits of AI and how it can be used in Power BI. Next, you'll focus on exploring and preparing your data for building AI projects and then progress to using prominent AI features already available in Power BI, such as forecasting, anomaly detection, and Q&A. Later chapters will show you how to apply text analytics and computer vision within Power BI reports. This will help you create your own Q&A functionality in Power BI, which allows you to ask FAQs from another knowledge base and then integrate it with PowerApps. Toward the concluding chapters, you'll be able to create and deploy AutoML models trained in Azure ML and consume them in Power Query Editor. After your models have been trained, you'll work through principles such as privacy, fairness, and transparency to use AI responsibly. By the end of this book, you'll have learned when and how to enrich your data with AI using the out-of-the-box AI capabilities in Power BI. What you will learnApply techniques to mitigate bias and handle outliers in your dataPrepare time series data for forecasting in Power BIPrepare and shape your data for anomaly detectionUse text analytics in Power Query EditorIntegrate QnA Maker with PowerApps and create an appTrain your own models and identify the best one with AutoMLIntegrate an Azure ML workspace with Power BI and use endpoints to generate predictionsWho this book is for This artificial intelligence BI book is for data analysts and BI developers who want to explore advanced analytics or artificial intelligence possibilities with their data. Prior knowledge of Power BI will help you get the most out of this book.

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Introducing Microsoft Power BI enables you to evaluate when and how to use Power BI. Get inspired to improve business processes in your company by leveraging the available analytical and collaborative features of this environment. Be sure to watch for the publication of Alberto Ferrari and Marco Russo's upcoming retail book, Analyzing Data with Power BI and Power Pivot for Excel (ISBN 9781509302765). Go to the book's page at the Microsoft Press Store here for more details:http://aka.ms/analyzingdata/details. Learn more about Power BI at https://powerbi.microsoft.com/.