Description

Book Synopsis

There are many webinars and training courses on Data Analytics for Internal Auditors, but no handbook written from the practitionerâs 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.



Table of Contents

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.

Data Analytics for Internal Auditors

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    Order before 4pm tomorrow for delivery by Tue 9 Jun 2026.

    A Paperback by Richard E. Cascarino

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      View other formats and editions of Data Analytics for Internal Auditors by Richard E. Cascarino

      Publisher: CRC Press
      Publication Date: 9/30/2020 12:00:00 AM
      ISBN13: 9780367658106, 978-0367658106
      ISBN10: 0367658100

      Description

      Book Synopsis

      There are many webinars and training courses on Data Analytics for Internal Auditors, but no handbook written from the practitionerâs 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.



      Table of Contents

      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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