東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Income statement semantic models = b...

Barber, Chris.

Linked to FindBook

Google Book

Amazon

博客來

Income statement semantic models = building enterprise-grade income statement models with Power BI /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Income statement semantic models/ by Chris Barber.
Reminder of title:	building enterprise-grade income statement models with Power BI /
Author:	Barber, Chris.
Published:	Berkeley, CA :Apress : : 2024.,
Description:	xxxiii, 433 p. :ill., digital ;24 cm.
[NT 15003449]:	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.
Contained By:	Springer Nature eBook
Subject:	Financial statements - Data processing. -
Online resource:	https://doi.org/10.1007/979-8-8688-0330-7
ISBN:	9798868803307

Income statement semantic models = building enterprise-grade income statement models with Power BI /
Barber, Chris.

Income statement semantic modelsbuilding enterprise-grade income statement models with Power BI /[electronic resource] :by Chris Barber. - Berkeley, CA :Apress :2024. - xxxiii, 433 p. :ill., digital ;24 cm.

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.

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

ISBN: 9798868803307

Standard No.: 10.1007/979-8-8688-0330-7doiSubjects--Uniform Titles:

Microsoft Power BI (Computer file)
Subjects--Topical Terms:

3753813
Financial statements
--Data processing.

LC Class. No.: HG4028.B2 / B37 2024

Dewey Class. No.: 658.1511

Income statement semantic models = building enterprise-grade income statement models with Power BI /
LDR:03482nmm a22003375a 4500 001 2388629
003 DE-He213
005 20240829130234.0
006 m d
007 cr nn 008maaau
008 250916s2024 cau s 0 eng d
020 $a 9798868803307 $q (electronic bk.)
020 $a 9798868803291 $q (paper)
024 7 $a 10.1007/979-8-8688-0330-7 $2 doi
035 $a 979-8-8688-0330-7
040 $a GP $c GP
041 0 $a eng
050 4 $a HG4028.B2 $b B37 2024
072 7 $a UMP $2 bicssc
072 7 $a COM051380 $2 bisacsh
072 7 $a UMP $2 thema
082 0 4 $a 658.1511 $2 23
090 $a HG4028.B2 $b B234 2024
100 1 $a Barber, Chris. $3 3753812
245 1 0 $a Income statement semantic models $h [electronic resource] : $b building enterprise-grade income statement models with Power BI / $c by Chris Barber.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2024.
300 $a xxxiii, 433 p. : $b ill., digital ; $c 24 cm.
347 $a text file $b PDF $2 rda
505 0 $a 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.
520 $a 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
630 0 0 $a Microsoft Power BI (Computer file) $3 3449087
650 0 $a Financial statements $x Data processing. $3 3753813
650 0 $a Business forecasting. $3 648526
650 0 $a Business intelligence $x Computer programs. $3 812285
650 0 $a Business $x Data processing. $3 527441
650 1 4 $a Microsoft. $3 3593799
650 2 4 $a Business IT Infrastructure. $3 2163249
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/979-8-8688-0330-7
950 $a Professional and Applied Computing (SpringerNature-12059)