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    1. Data och IT
    2. Databaser

    Data Analytics for Accounting ISE

    AvVernon J. Richardson,Katie Terrell

    Häftad, Engelska, 2022

    952 kr

    Tillfälligt slut

    Beskrivning

    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.

    Produktinformation

    • Utgivningsdatum:2022-03-22
    • Mått:203 x 251 x 25 mm
    • Vikt:1 038 g
    • Format:Häftad
    • Språk:Engelska
    • Antal sidor:642
    • Upplaga:3
    • Förlag:McGraw-Hill Education
    • ISBN:9781265094454

    Utforska kategorier

    • Databaser inom Data och IT
    • Redovisning inom Ekonomi och Ledarskap

    Mer om författaren

    Vernon J. Richardson is a Distinguished Professor of Accounting and the G. William Glezen Chair in the Sam M. Walton College of Business at the University of Arkansas and a visiting professor at Baruch College. He received his BS. Master’s of Accountancy, and MBA from Brigham Young University and a PhD in accounting from the University of Illinois at Urbana-Champaign. He has taught students at the University of Arkansas, University of Illinois, Brigham Young University, and University of Kansas and internationally at Chinese University of Hong Kong Shenzhen, Aarhus University, the China Europe International Business School (Shanghai), Xi'an Jiaotong Liverpool University, and the University of Technology Sydney.Dr. Richardson is a member of the American Accounting Association. He has served as president of the American Accounting Association Information Systems section. He previously served as an editor of The Accounting Review and is currently an editor at Accounting Horizons. He has published articles in The Accounting Review, Journal of Information Systems, Journal of Accounting and Economics, Contemporary Accounting Research, MIS Quarterly, International Journal of Accounting Information Systems, Journal of Management Information Systems, Journal of Operations Management, and Journal of Marketing. Dr. Richardson is also a co-author of McGraw-Hill’s Introduction to Data Analytics for Accounting, Data Analytics for Accounting and Introduction to Business Analytics textbooks. Katie L. Terrell is an instructor in the Sam M. Walton College of Business at the University of Arkansas. She received her B.A. degrees in English Literature and in the Spanish Language from the University of Central Arkansas, and received her MBA from the University of Arkansas. She expects a doctoral degree by 2019. She has taught students at the University of Arkansas, Soochow University (Suzhou, China), the University College Dublin (Ireland), and at Duoc UC, a branch of the Catholic University of Chile (a del Mar, Chile). She is a member of the American Accounting Association and has published a Statement on Management Accounting for the Institute of Management Accountants on managing organizational change in operational change initiatives. She has recently been recognized for her innovative teaching by being the recipient of the Mark Chain/FSA Teaching Award for innovative graduate-level accounting teaching practices in 2016. She has worked with Tyson Foods, where she held various Information System roles focusing on business analysis, project management for ERP implementations and upgrades, and organizational change management. Ryan A. Teeter is a Clinical Assistant Professor of Accounting in the Katz Graduate School of Business at the University of Pittsburgh. He teaches accounting information systems, auditing, and accounting data analytics. Prior to receiving his PhD in Accounting Information Systems from Rutgers University, he worked at Google in Mountain View, California. He has since worked with internal audit organizations at Siemens, Procter Gamble, Alcoa/Arconic and Fedex helping to develop robotic process automation programs and data analytic solutions. Dr. Teeter is a member of the American Accounting Association and has published articles in the Journal of Strategic Technologies in Accounting and Issues in Accounting Education. He has received grant funding for data analytics research from PwC.

    Innehållsförteckning

    • 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