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 designin...

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Detalles Bibliográficos
Autor principal: Barber, Chris (-)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berkeley, CA : Apress 2024.
Edición:1st ed. 2024.
Materias:
Microsoft Power BI (Computer file)
Financial statements > Data processing.
Business forecasting.
Business intelligence > Computer programs.
Business > Data processing.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009845438406719
Tabla de Contenidos:
  • Part I: Modelling and the Income Statement
  • Chapter 1: What is an income statement semantic model?
  • Chapter 2: How to Construct an Income Statement
  • Chapter 3: Building a Reusable Solution
  • Chapter 4: Why model the income statement?
  • Part II: Calculating Account Balances - Chapter 5: Conceptual Account Balance Models
  • Chapter 6: Logical Account Balance Models
  • Chapter 7: The Trial Balance Semantic Model
  • Chapter 8: A Journal Entry Semantic Model
  • Part III: Producing External Income Statement Semantic Models
  • Chapter 9: The Four Subtotal and Subset Types
  • Chapter 10: External Reporting Logical Models
  • Chapter 11: External Reporting Semantic Models
  • Part IV: Producing Internal Income Statement Sematic Models
  • Chapter 12: Internal Reporting Logical Models
  • Chapter 13: Internal Reporting Semantic Models
  • Chapter 14: Security and Self-service Considerations
  • Chapter 15: Review of the Sixteen Challenges.

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