Income Statement Semantic Models: Building Enterprise Grade Income Statement Models with Power BI

Income Statement Semantic Models: Building Enterprise-Grade Income Statement Models with Power BI 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 LearnModeling and the income statement: Learn what modelling the income statement entails, why it is important, and how income statements are constructedCalculating account balances: Learn how to optimally calculate account balances using a Star SchemaProducing 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 entriesProducing 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 considerationsWho This Book Is ForTechnical 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 Autor: Chris Barber Wydawnictwo: Springer Rok wydania: 2024 Okładka: miękka Liczba stron: 433 Wymiary: 23.5 x 15.5 cm Ilustracje: 247 Illustrations, color; 22 Illustrations, black and white; XXXIII, 433 p. 269 illus., 247 illus. in color. Język: angielski ISBN: 9798868803291