Income Statement Semantic Models with Power Bi: Build Enterprise-Grade Income Statement Models

by Barber, Chris
ISBN: 9798868803291
Availability:
null

Available Offers


Pickup at {0} Out of stock at {0} Check other stores
FREE
Ship to Me
$3.99

Overview

This comprehensive guide teaches you how to build income statement (P&L) semantic models. Author Chris Barber, a BI consultant, Microsoft MVP, and chartered accountant (CGMA, ACMA), helps you master everything you need to know, from building conceptual models to writing DAX. You will learn how to build a re-usable solution based on the trial balance and expand upon this to slice-and-dice the income statement from multiple perspectives. You will also learn about security and self-service considerations, including how to optimize your semantic model for Excel.


What You Will Learn

  • Modelling and the income statement: What modelling the income statement entails, why it is important, and how income statements are constructed
  • Measuring line-items on the income statement: How to optimally calculate line-items using a Star Schema
  • Producing the external income statement: How to produce external income statements in their entirety, by analyzing a range of perspectives and drilling in to reveal the underlying accounts and journal entries
  • Extending the income statement for internal reporting: How to create multiple income statement layouts and contextualize financial information by including percentages and non-financial information
  • Optimize the semantic model for self-service


Who This Book Is For

Technical users (solution architects, Power BI developers) struggling to produce income statement semantic models due to complex modeling requirements and requisite knowledge of the accounting process; and finance users producing income statements in Excel, but reaching the limitations of row count, inability to automatically update, or ability to secure appropriately using two-factor authentication
  • Format: Trade Paperback
  • Author: Barber, Chris
  • ISBN: 9798868803291
  • Condition: New
  • Number Of Pages: 190
  • Publication Year: 2024
Language: English