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Home All Courses DAIA Data Analytics in Internal Audit
4.8

DAIA Data Analytics in Internal Audit

2 alternative location(s) available

Course Overview

A practical hands-on approach to conducting Data Analytics has become a necessity since the spread of IT systems has made it a pre-requisite that auditors as well as management have the ability to examine high volumes of data and transaction in order to determine patterns and trends. In addition, the increasing need to continuously monitor and audit IT systems has created an imperative for the effective use of appropriate data mining tools.
While a variety of powerful tools are readily available today, the skills required to utilize such tools are not. Not only must the correct testing techniques be selected but the effective interpretation of outcomes presented by the software is essential in the drawing of appropriate conclusions based on the data analysis.
This means that the users of such tools must gain skills not only in the technical implementation of the software, but also in the understanding of structures and meanings of corporate data including the ability to determine the information requirements for the effective management of business.

2 alternative location(s) available

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5 Key Takeaways

1

Learn the business Risks of using IT, related controls and IS assurance and audit concepts

What does an IT Audit engagement involve and approach to risk based IS audits

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3

Overview of IS assurance and audit standards, tools and techniques

Planning & performing riskbased IS audit procedures

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An understanding of the scope of the emerging technology concepts, related issues & business risks

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05

See What’s Inside Our 2020 Catalog

Course Outline

DAY 1

Introduction to Data Analysis

This session will introduce the reader to the principles of information flow within organizations as well as data analytic methodologies and terminology. The focus will be on developing an understanding of where critical data exists for analysis, the obtaining of access and the selection of the appropriate analytical techniques.
We will examine the differences between a given set of data in the standard benchmark in terms of central tendency, variation and shape of curve. In addition we will examine the fundamental principles of Baysian probability theory. In general, this is a methodology used to trying to clarify the relationship between theory and evidence. It attempts to demonstrate how the probability that the theory is true is affected by a new piece of evidence. This can be critical to auditors in drawing conclusions about large populations based upon small samples drawn.

Understanding Sampling

This session will cover the fundamental assumptions underlying the use of sampling techniques, the nature of populations and the use of variables. Distribution frequencies and central tendency measurement will be covered as well as the impact on analysis of distribution characteristics. It will also examine the differences between judgmental and statistical sampling, the applicability of both in audit practice, and the dangers inherent in confusing the two.
The differences in selection methods will be covered as well as their impact on the analysis and interpretation possible within the sampling methods.

  • Judgmental vs Statistical Sampling
  • Probability theory in Data Analysis
  • Types of Evidence
  • Population Analysis
  • Correlations and Regressions

DAY 2

Applying Differing Analytical Techniques

This session will examine typical CAATs in common use in the selection of the appropriate technique based upon the type of evidence and the audit objective. Included will be the dangers to the auditor inherent in pre-judgment of expected results and the subsequent distortion of the analysis based upon these pre-conceptions. It will also examine the audit methodologies for the analysis of Big data. Big data is a term given to large datasets containing a variety of data types. Big data analysis allows the auditor to seek for hidden patterns and identify concealed correlations, market trends and other data inter-relationships which can indicate areas for improved operational efficiencies within business processes.

Topics covered in this session include:

  • Big Data Structures
  • OLAP
  • Statistical Analysis and Big Data
  • Substantive Analytical Procedures
  • Validation
  • Questionnaire Analysis and Likert Scales
  • Statistical Reliability Analysis

DAY 3

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LEORON - Professional Development Institute

Built upon the strong experience in the manufacturing sector, which the founders developed in Sweden during the 90’s global expansion, LEORON evolved into a comprehensive training institute, offering training and development solutions in all strategic corporate functions, including corporate finance, HR, SCM, operations, and engineering.

With strategic distribution of our offices in leading locations, such as Dubai, Riyadh, Jonkoping, Skopje, Accra, and Almaty, our team of experts delivers approximately 500 courses annually, and roughly 10000 professionals are equipped with appropriate education and the latest insights in a wide assortment of industries across the EMEA region.

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Who Should Attend?

This highly practical and interactive course has been specifically designed for:

  • Internal Audit Professionals, Chief Audit Executives
  • IT Management Professionals
  • Risk Officers & strategic management members
  • Internal control professionals

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Most of our public courses are delivered in English language. You need to be proficient in English to be able to fully participate in the workshop and network with other delegates. For in-house courses we have the capability to train in Arabic, Dutch, German and Portuguese.

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