Data analytics for internal auditors / Richard E. Cascarino
Series: Internal audit and IT auditBoca Raton, Florida, USA : CRC Press, ©2017Description: xxii, 417 pages : illustrations ; 24 cmContent type:- text.
- 9781498737159
- 1498737153
- 23 657.458/C26
- HF5668 .C373 2017
- CBA
Item type | Current library | Collection | Call number | Status | Barcode | |
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College Library General Circulation Section | GC | CBA 657.458/C26 (Browse shelf(Opens below)) | Available | 83926 |
Browsing College Library shelves, Shelving location: General Circulation Section, Collection: GC Close shelf browser (Hides shelf browser)
CBA 657.45/B38 Auditing cases : | CBA 657.45/K72 Contemporary auditing : | CBA 657.45/R35 Auditing and assurance services / | CBA 657.458/C26 Data analytics for internal auditors / | CBA 657.458/M72 Brink's modern internal auditing : | CBA 657.458/M94 Operational auditing : | CBA 657.458/W46 Principles of fraud examination / |
"An Auerbach book."
Includes bibliographical references and index
Chapter 1. Introduction to data analysis -- chapter 2. Understanding sampling -- chapter 3. Judgmental versus statistical sampling -- chapter 4. Probability theory in data analysis -- chapter 5. Types of evidence -- chapter 6. Population analysis -- chapter 7. Correlations, regressions, and other analyses -- chapter 8. Conducting the audit -- chapter 9. Obtaining information from IT systems for analysis -- chapter 10. Use of computer-assisted audit techniques -- chapter 11. Analysis of big data -- chapter 12. Results analysis and validation -- chapter 13. Fraud detection using data analysis -- chapter 14. Root cause analysis -- chapter 15. Data analysis and continuous monitoring -- chapter 16. Continous auditing -- chapter 17. Financial analysis -- chapter 18. Excel and data analysis -- chapter 19. ACL and data analysis -- chapter 20. IDEA and data analysis -- chapter 21. SAS and data analysis -- chapter 22. Analysis reporting -- chapter 23. Data visualization and presentation -- chapte 24. Conclusion Introduction to data analysis -- Understanding sampling -- Judgmental versus statistical sampling -- Probability theory in data analysis -- Types of evidence -- Population analysis -- Correlations, regressions, and other analyses -- Conducting the audit -- Obtaining information from IT systems for analysis -- Use of computer-assisted audit techniques -- Analysis of big data -- Results analysis and validation -- Fraud detection using data analysis -- Root cause analysis -- Data analysis and continuous monitoring -- Continous auditing -- Financial analysis -- Excel and data analysis -- ACL and data analysis -- IDEA and data analysis -- SAS and data analysis -- Analysis reporting -- Data visualization and presentation -- Conclusion.
Providing a reference guide for IT and Internal Auditors as well as Fraud Examiners, this book presents information written from the practitioner's viewpoint covering not only the need and the theory, but a practical hands-on approach to conducting data analytics. --
In English.
UCLA Library - CDL shared resource.
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