In data analytics, cleaning the data is a crucial step where the auditor eliminates redundancies, corrects inconsistencies, and removes errors to ensure accurate analysis. This step is taken before analyzing the data to identify high-risk areas and relevant processes.

Correct Answer (C - Cleaning the Data in Preparation for Determining Involved Processes)

Data cleaning involves:

Removing duplicate entries to prevent misinterpretation.

Standardizing data formats for consistency.

Handling missing or inaccurate values to ensure reliability.

This step prepares the data for analysis and identification of high-risk processes.

The IIA’s GTAG 16: Data Analysis Technologies emphasizes data cleaning as a critical part of internal audit analytics.

Why Other Options Are Incorrect:

Option A (Normalizing data in preparation for analyzing it):

Normalization refers to structuring data efficiently (e.g., in databases) but does not necessarily involve eliminating redundancies in the way described.

Option B (Analyzing data in preparation for communicating results):

The auditor is still in the data preparation phase, not the analysis or reporting phase.

Option D (Reviewing data prior to defining the question):

The auditor is already working with data. Defining questions typically happens before data collection.

GTAG 16: Data Analysis Technologies – Covers data preparation, cleaning, and analytics in internal auditing.

IIA Practice Guide: Data Analytics in Internal Auditing – Outlines best practices for data validation and cleaning.

Step-by-Step Explanation:IIA References for Validation:Thus, cleaning the data (C) is the correct answer, as it ensures data integrity before identifying relevant processes and risks.