TY  - BOOK
AU  - Richardson, Vernon J.
AU  - Teeter, Ryan
AU  - Terrell, Katie
TI  - Data analytics for accounting
SN  - 9789390219667
U1  - 657.0285 
PY  - 2021///
CY  - Chennai
PB  - McGraw Hill Education (India) Pvt. Ltd.
KW  - Accounting - Data processing
KW  - Decision support systems
KW  - Industrial management - Statistical methods
N1  - Table of content

Chapter 1 Data Analytics for Accounting and Identifying the Questions 
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
Chapter 12 Accounting Analytics in India


Appendix A Basic Statistics Tutorial
Appendix B Accessing the Excel Data Analysis Toolpak 
Appendix C Excel (Formatting, Sorting, Filtering, and PivotTables) 
Appendix D SQL Part 1
Appendix E SQLite 
Appendix F Power Query 
Appendix G Tableau
Appendix H SQL Part 2 
Appendix I Power BI 
Appendix J Dillard’s ER Diagram
Appendix K Data Dictionaries
N2  - OVERVIEW
Data Analytics for Accounting, 2e is designed to provide the readers with the necessary tools and skills to successfully perform data analytics. Using Isson's data analytics model, the IMPACT Cycle, the text provides a conceptual framework to help readers think through the steps needed to provide data-driven insights and recommendations. Each chapter integrates lab exercises that provide multiple datasets and tutorials to give students hands-on experience working with different types of data. The book also emphasizes on the application and usability of different tools for data analysis, such as Microsoft Excel, Microsoft Access (including SQL) Tableau, IDEA, XBRL, and Weka
ER  -