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.

Introduction to Business Analytics recognizes that students need to develop the skills to ask the right questions, learn to use common workplace tools (such as Excel (R), Tableau (R), and Power BI (R)) to examine and analyze data, and interpret results accurately and effectively to make business decisions. Richardson 1e provides a framework for developing a business analytics mindset called the SOAR analytics model which is composed of four steps- Specify the question, Obtain the data, analyze the data, and report the results. This model is used throughout the text in conjunction with the various types of data analysis that analysts need to perform. The lab activities, which appear at the end of each chapter, follow this framework to reinforce the analytical process. A capstone in the final chapter provides three projects that apply the complete SOAR model.