Exam Certified AI Associate topic 1 question 12 discussion

Age is the only data quilty dimension in the options

Data quality dimensions: Age, Completeness, Accuracy, Consistency, Duplication, Usage. https://trailhead.salesforce.com/content/learn/modules/data_quality/data_quality_assess_your_data?trailmix_creator_id=strailhead&trailmix_slug=prepare-for-your-salesforce-ai-associate-credential

When aiming to predict shoe demand using historical sales data and regional characteristics, ensuring reliable data is essential. Reliability in data quality refers to the degree to which data is accurate, consistent, and trustworthy, directly impacting the effectiveness of AI models. Inaccurate or inconsistent data can lead to flawed predictions, adversely affecting decision-making processes. While volume (the amount of data) and age (the recency of data) are important considerations, they are secondary to reliability. A large dataset is beneficial only if the data is reliable; similarly, recent data is valuable only when its accuracy and consistency are ensured. Therefore, among the options provided, A. Reliability is the most critical data quality dimension to focus on for accurately predicting shoe demand.

Age is the solution

Reliability accounts for consistency and accuracy

I asked this question to chatGPT and here is the reply The correct answer is B. Reliability. For Cloud Kicks to use an AI model to accurately predict shoe demand, reliable data is essential. Reliability refers to the consistency and accuracy of the data, ensuring that the historical sales data and regional characteristics are trustworthy and can lead to accurate predictions. Here’s why the other options are less relevant: A. Age: While the age or recency of data can be important, it is not the most essential data quality dimension in this case. Older data can still be useful if it's reliable and relevant. C. Volume: Having a large amount of data (volume) is helpful for AI models, but without reliability, even large datasets can lead to poor predictions. Thus, reliable data is crucial to ensure the AI model makes accurate and consistent predictions.

I believe letter B because "Reliability" is kinda synonym for "Accuracy" and "Consistency", which are both more related to the theme of the question than "Age".

A is the correct and only choice that is a "Data quality dimension". I get how B seems like it would be correct but this question isn't asking you to make up your own "data quality dimensions" its asking out of the 6 (Age, Completeness, Accuracy, Consistency, Duplication, Usage) which is appropriate here. Please stop confidently writing the wrong answer (B) with no explanation and no evidence.

B. Reliability

B. Reliability

Age only data quilty dimension in the option