As it relates to the data analytics process, which of the following best describes the purpose of an internal auditor who cleaned and normalized data?
As it relates to the data analytics process, which of the following best describes the purpose of an internal auditor who cleaned and normalized data?
The purpose of cleaning and normalizing data for an internal auditor is to ensure the data is consistent and usable for a specific purpose. This process involves making sure that data fields are consistent, which helps in maintaining data integrity and accuracy, and ensures that the data can be reliably used for analysis or other specific purposes. While eliminating duplicate information and organizing data to minimize useless information are part of the data cleaning process, the overall goal is best described by ensuring data consistency and usability, which is clearly stated in option D.
It's A. Question says "CLEANED and normalized data". All the other options are examples of data that is only normalized. Cleaning includes getting rid of duplicate info - Normalizing CAN entail that task as well.
Data used for analysis must be correct, consistent, complete, free from duplication, with inaccurate or irrelevant parts deleted. so why answer not C?
Now I'm thinking it could be 'D' based on the article. 'A' is too simple and applies to CLEANING data. 'B' doesn't make sense. 'C' is not right because you're not supposed to identify and then correct any anomalies - you're supposed to look for anomalies AFTER you clean/normalize the data and then find the cause for the anomalies. According to that Reference article, the one that answers the question of what BEST describes the auditor's purpose for cleaning/normalizing data (in other words: WHY did the auditor clean/normalize data), it makes sense to say that that "The auditor cleaned and normalized the data so that the data fields were consistent and could be used for a specific purpose".
D is regard consistency of data so not correct. Cleansing data includes identifying and removing duplicate data and identifying whether identically named data fields from different systems have identical or different meanings. Normalizing data is the process of organizing data in order to reduce the potential of redundancy and to facilitate the use of the data for specific purposes. Normalizing also allows for the identification of anomalies, which might represent actual problems or potential opportunities. so the answer is C
The only problem though is that 'C' says for anomalies to be identified AND CORRECTED. If it didn't have the "and corrected" portion to the answer, I'd agree with you. But it says "anomalies were identified and corrected". Normalization does not include correcting the anomalies. The article states that outliers (another term for anomalies) need to be investigated for the cause AFTER the data has been cleaned/normalized. Nowhere does it state to CORRECT them. Although D is definitely not overly comprehensive, it does answer the reason/purpose for why an internal auditor cleaned/normalized data.
Why not d