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Data Analytics for Accounting ISE

Autor Vernon Richardson, Katie Terrell, Ryan Teeter
en Limba Engleză Paperback – 22 mar 2022
Data Analytics is changing the business world—data simply surrounds us, which means all accountants must develop data analytic skills to address the needs of the profession in the future. Data Analytics for Accounting 3e is designed to prepare your students with the necessary tools and skills they need to successfully perform data analytics through a conceptual framework and hands-on practice with real-world data. Using the IMPACT Cycle, the authors provide a conceptual framework to help students think through the steps needed to provide data-driven insights and recommendations.

Once students understand the foundation of providing data-driven insights, they are then provided hands-on practice with real-world data sets and various data analysis tools which students will use throughout the rest of their career. The data analysis tools are structured around two tracks—the Microsoft track (Excel, Power Pivot, and Power BI) and a Tableau track (Tableau Prep and Tableau Desktop). Using multiple tools allows students to learn which tool is best suited for the necessary data analysis, data visualization, and communication of the insights gained. Data Analytics for Accounting 3e is a full-course data analytics solution guaranteed to prepare your students for their future careers as accountants.
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Specificații

ISBN-13: 9781265094454
ISBN-10: 1265094454
Pagini: 642
Dimensiuni: 203 x 252 x 25 mm
Greutate: 1.04 kg
Ediția:3
Editura: McGraw Hill Education
Colecția McGraw-Hill
Locul publicării:United States

Cuprins

Chapter 1: Data Analytics for Accounting and Identifying theQuestions
Chapter 2: Mastering the Data
Chapter 3: Performing the Test Plan and Analyzing theResults
Chapter 4: Communicating Results and Visualizations
Chapter 5: The Modern Accounting Environment
Chapter 6: Audit Data Analytics
Chapter 7: Managerial Analytics
Chapter 8: Financial Statement Analytics
Chapter 9: Tax Analytics
Chapter 10: Project Chapter (Basic)
Chapter 11: Project Chapter (Advanced): Analyzing Dillard’sData to Predict Sales Returns
Appendix A: Basic Statistics Tutorial
Appendix B: Excel (Formatting, Sorting, Filtering, andPivotTables)
Appendix C: Accessing the Excel Data Analysis Toolpak
Appendix D: SQL Part 1
Appendix E: SQL Part 2
Appendix F: Power Query in Excel and Power BI
Appendix G: Power BI Desktop
Appendix H: Tableau Prep Builder
Appendix I: Tableau Desktop
Appendix J: Data Dictionaries