03964nam a22004455i 4500001001800000003000900018005001700027007001500044008004100059020003700100024003500137050001600172072001600188072002300204072001500227100008300242245014700325250001800472264005400490300007000544336002600614337002600640338003600666347002400702505095000726520146301676650002403139650003003163650004703193650001503240650003903255710003403294773002603328776003603354776003603390856004603426912001403472912001503486999001703501979-8-8688-0330-7DE-He21320251030112920.0cr nn 008mamaa240829s2024    xxu|    s    |||| 0|eng d  a97988688033079979-8-8688-0330-77 a10.1007/979-8-8688-0330-72doi 4aQA76.76.M52 7aUMP2bicssc 7aCOM0513802bisacsh 7aUMP2thema1 aBarber, Chris.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut98318110aIncome Statement Semantic Modelsh[electronic resource] :bBuilding Enterprise-Grade Income Statement Models with Power BI /cby Chris Barber.  a1st ed. 2024. 1aBerkeley, CA :bApress :bImprint: Apress,c2024.  aXXXIII, 433 p. 269 illus., 247 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda0 aPart 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.  aThis 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 . 0aMicrosoft software. 0aMicrosoft .NET Framework. 0aInformation technologyxManagement.95722314aMicrosoft.24aBusiness IT Infrastructure.9697442 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z979886880329108iPrinted edition:z979886880331440uhttps://doi.org/10.1007/979-8-8688-0330-7  aZDB-2-CWD  aZDB-2-SXPC  c62856d62856