Overview

Why Attend

Processes are becoming more complex; and simple audit techniques and random audit samples are not enough anymore to provide factual evidence to draw conclusions. Given this, it is only through proper data analysis and smart sampling that auditors can perform their responsibilities in an effective and efficient way.

This course develops critical skills in analyzing and interpreting data, which are essential in today's data-driven world. The course equips participants with knowledge and techniques to identify patterns, trends, and relationships in data, enabling them to make strategic decisions that benefit their organizations. Additionally, participants gain skills to confidently design and execute effective audit sampling plans that can greatly improve the efficiency and effectiveness of the audit process.

Course Methodology

Through group exercises, case studies and real-time data bundles, participants will turn raw data into knowledge to understand patterns and identify red flags, or deviations from procedures and standards. Moreover, participants will go through several audit sampling techniques that will help them develop representative and efficient sample sizes that can be applied in their day-to-day missions.

Course Objectives

By the end of the course, participants will be able to:

Demonstrate a comprehensive understanding of data analysis techniques
Understand the impact of data analysis on audit sampling
Use statistical tools to analyze information, manipulate data and conduct audit sampling
Apply different audit sampling methods to different scenarios
Identify data anomalies and deviations in audit results to simplify the reporting process

Target Audience

This course is suitable for all Internal Auditors, and those involved in the internal auditing process including, but not limited to, internal controllers, risk officers, external auditors and compliance officers from all levels.

Target Competencies

Data mining
Mitigating risks
Data analysis
Understanding trends
Searching for anomalies

Course Outline

Introduction to data analysis
- Definition and history
- Current technology, the growing availability of data, and increasing challenges
- The impact of vast volumes of data
- Understanding when and how to corroborate data
- Rethinking the value and usage of data
- Getting real value from the data
The different sampling methods
- Sampling and non-sampling risks
- Statistical and non-statistical sampling
- Random sample vs. population census
- Sampling method vs. sample size
- Benefits and risks of sampling techniques such as:
  - Random sampling
  - Stratified sampling
  - Interval sampling
  - Subjective sampling
  - Block sampling
  - Systematic sampling
  - Dollar unit sampling
  - Stop or go sampling
Comparison and benchmarking
- Practice Advisory 2320
- Institute of Internal Auditors (IIA) recommendations and publications
- Performance benchmarking
- The evolution of big data
- Evaluating the effectiveness of new data analysis techniques
- Peer benchmarking
Data mining vs. audit sampling
- Different data analysis techniques and selecting the sample
- Employing methods for adjusting sampling size
- Simple excel functions and queries to perform analyses
- Incorporating fraud red flags in the audit sampling
- Practice combining results for different scenarios
Identifying data anomalies and deviations
- Fundamental concepts of data anomalies and deviations
- Importance and impact on business operations
- Techniques for identifying, cleaning, and transforming data
- Types such as outliers, missing values, and errors
- How to identify, analyze and highlight them
  - Statistical methods
  - Visualization techniques to identify and highlight data anomalies and deviation
- Real-world examples and cases in in different industries and business domains

Schedule & Fees

2026 Schedule & Fees

There are no public sessions remaining for the course this year. Please contact us if you wish to have a customized in-house session, or to find out how an additional public session can be scheduled.

2027 Schedule & Fees

17 - 21 Jan, 2027

English

Per participant USD 2,900

17 - 21 Jan, 2027

Arabic

Per participant USD 2,900

31 Jan - 4 Feb, 2027

English

Per participant USD 2,900

31 Jan - 4 Feb, 2027

Arabic

Per participant USD 2,900

18 - 22 Apr, 2027

English

Per participant USD 2,900

18 - 22 Apr, 2027

Arabic

Per participant USD 2,900

2 - 6 May, 2027

English

Per participant USD 2,900

2 - 6 May, 2027

Arabic

Per participant USD 2,900

18 - 22 Jul, 2027

English

Per participant USD 2,900

18 - 22 Jul, 2027

Arabic

Per participant USD 2,900

1 - 5 Aug, 2027

English

Per participant USD 2,900

1 - 5 Aug, 2027

Arabic

Per participant USD 2,900

17 - 21 Oct, 2027

English

Per participant USD 2,900

17 - 21 Oct, 2027

Arabic

Per participant USD 2,900

31 Oct - 4 Nov, 2027

English

Per participant USD 2,900

31 Oct - 4 Nov, 2027

Arabic

Per participant USD 2,900

Data Analysis for Internal Auditing

Overview

Why Attend

Course Methodology

Course Objectives

Target Audience

Target Competencies

Course Outline

Schedule & Fees

2026 Schedule & Fees

2027 Schedule & Fees