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ISBN10: 1264444907 | ISBN13: 9781264444908

* The estimated amount of time this product will be on the market is based on a number of factors, including faculty input to instructional design and the prior revision cycle and updates to academic research-which typically results in a revision cycle ranging from every two to four years for this product. Pricing subject to change at any time.
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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.
Chapter 2: Mastering the Data
Chapter 3: Performing the Test Plan and Analyzing the Results
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’s Data to Predict Sales Returns
Appendix A: Basic Statistics Tutorial
Appendix B: Excel (Formatting, Sorting, Filtering, and PivotTables)
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
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