There are many webinars and training courses on Data Analytics for Internal Auditors, but no handbook written from the practitioner's viewpoint covering not only the need and the theory, but a practical hands-on approach to conducting Data Analytics. The spread of IT systems makes it necessary that auditors as well as management have the ability to examine high volumes of data and transactions to determine patterns and trends. The increasing need to continuously monitor and audit IT systems has created an imperative for the effective use of appropriate data mining tools. This book takes an…mehr
There are many webinars and training courses on Data Analytics for Internal Auditors, but no handbook written from the practitioner's viewpoint covering not only the need and the theory, but a practical hands-on approach to conducting Data Analytics. The spread of IT systems makes it necessary that auditors as well as management have the ability to examine high volumes of data and transactions to determine patterns and trends. The increasing need to continuously monitor and audit IT systems has created an imperative for the effective use of appropriate data mining tools. This book takes an auditor from a zero base to an ability to professionally analyze corporate data seeking anomalies.
Richard E. Cascarino, MBA, CIA, CISM, CFE, CRMA, is well-known in international auditing. He is a principal of Richard Cascarino & Associates, with over 31 years experience in audit training and consultancy. He is a regular speaker to National and International conferences and has presented courses throughout Africa, Europe, the Middle East and the USA.Richard is a Past President of the Institute of Internal Auditors in South Africa, was the founding Regional Director of the Southern African Region of the IIA-Inc and is a member of ISACA, and the Association of Certified Fraud Examiners, where he is a member of the Board of Regents for Higher Education.Richard was Chairman of the Audit Committee of Gauteng cluster 2 (Premier's office, Shared Services and Health) in Johannesburg and is currently the Chairman of the Audit and Risk Committee of the Department of Public Enterprises in South Africa.He is also a visiting Lecturer at the University of the Witwatersrand, author of the book "Internal Auditing: An Integrated Approach," now in its third edition. This book is extensively used as a university textbook worldwide. In addition, he is the author of the "Auditor's Guide to IT Auditing," now in its 2nd edition and "Corporate Fraud and Internal Control: A Framework for Prevention." He is also a contributor to all four editions of QFINANCE, the UItimate Resource.
Inhaltsangabe
Introduction to Data Analysis. Understanding Sampling. Judgmental vs Statistical Sampling. Probability theory in Data Analysis. Types of Evidence. Population Analysis. Correlations and Regressions. Conducting the Audit. Obtaining Information from IT Systems for Analysis. Use of Computer Assisted Audit Techniques. Analysis of Big Data. Results Analysis and Validation. Root Cause Analysis. Data Analysis and Continuous Monitoring. Continuous Auditing. Financial Analysis. Excel and Data Analysis. ACL and Data Analysis. IDEA and Data Analysis. Analysis Reporting.
Introduction to Data Analysis. Understanding Sampling. Judgmental vs Statistical Sampling. Probability theory in Data Analysis. Types of Evidence. Population Analysis. Correlations and Regressions. Conducting the Audit. Obtaining Information from IT Systems for Analysis. Use of Computer Assisted Audit Techniques. Analysis of Big Data. Results Analysis and Validation. Root Cause Analysis. Data Analysis and Continuous Monitoring. Continuous Auditing. Financial Analysis. Excel and Data Analysis. ACL and Data Analysis. IDEA and Data Analysis. Analysis Reporting.
Introduction to Data Analysis. Understanding Sampling. Judgmental vs Statistical Sampling. Probability theory in Data Analysis. Types of Evidence. Population Analysis. Correlations and Regressions. Conducting the Audit. Obtaining Information from IT Systems for Analysis. Use of Computer Assisted Audit Techniques. Analysis of Big Data. Results Analysis and Validation. Root Cause Analysis. Data Analysis and Continuous Monitoring. Continuous Auditing. Financial Analysis. Excel and Data Analysis. ACL and Data Analysis. IDEA and Data Analysis. Analysis Reporting.
Introduction to Data Analysis. Understanding Sampling. Judgmental vs Statistical Sampling. Probability theory in Data Analysis. Types of Evidence. Population Analysis. Correlations and Regressions. Conducting the Audit. Obtaining Information from IT Systems for Analysis. Use of Computer Assisted Audit Techniques. Analysis of Big Data. Results Analysis and Validation. Root Cause Analysis. Data Analysis and Continuous Monitoring. Continuous Auditing. Financial Analysis. Excel and Data Analysis. ACL and Data Analysis. IDEA and Data Analysis. Analysis Reporting.
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