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The Art of Gathering and Validating Data for Analytics

Course Description

Print-friendly Course Description and Outline

​Evidence gathering is a critical step in the internal audit process. As internal audit teams gain agility, the focus turns toward data analytics. Improving data gathering and validation processes are key to building meaningful analytics. For some internal audit teams obtaining the data is half the battle.

Who will benefit from this course?

This program is for audit leaders and internal auditors looking for a basic understanding of data gathering, validation, and analysis techniques.

Course Objectives

In this course, participants will:

  • Examine data literacy primary competencies.
  • Explore common data gathering techniques.
  • Identify where data exists and how (and when) to request it.
  • Recognize the importance of validating data before starting analysis and methods to validate and deal with exceptions and outliers.
  • Discuss the key steps in data analysis.
  • Describe the key differences between continuous monitoring and continuous auditing.
Course Duration: 0.5 day(s)
CPEs Available: 4
Knowledge Level: Basic
Field of Study: Auditing
Prerequisites: 
​None
Advance Preparation: 
​None
Delivery Method: eLearning (Group-Internet-Based); On-site Training (Group-Live); Seminar (Group-Live); Live Stream

​Data Literacy Core Competency

  • Examine the 5 competencies via the lens of data collection.

Data Gathering Techniques

  • Common terms and their business meaning.
  • Good practices on how to set up a data and information request process between internal audit and IT.
  • Data location specific considerations.
  • Considerations regarding sensitive and proprietary data including DEI, PII, PHI, PAN, and ESG.
  • Considerations regarding shadow IT (end-users).
  • Tips for communicating with data scientists and stewards.
  • Differences in approach by organizational size.
  • Differences in approach by internal audit size and skill sets.

Data Validation

  • Ensuring accuracy and completeness.
  • Checking for duplicates.
  • Looking of other data exceptions or anomalies.
  • Differences in approach by organizational size.
  • Differences in approach by internal audit size and skill sets.

Data Analysis Primer

  • Processes for conducting data analysis.
  • Selection of population or sample.
  • Common characteristics across data collection tools.
  • Tips for ensuring integrity is maintained during the analysis process.
  • Methods of confirming validity of analysis results.
  • Reliance on continuous monitoring efforts by the business, IT, or a third party provider.
  • Using data analytics for continuous auditing.
  • Using data analytics for continuous assurance
  • Differences in approach by organizational size.
  • Differences in approach by internal audit size and skill sets.

​Most courses can be delivered through on-site training. You might be surprised that the organization leading the profession is just as committed to the delivery of affordable training.

Contact us by calling +1-407-937-1388 or send an e-mail to GetTraining@theiia.org.

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