Free CompTIA DA0-002 Actual Exam Questions - Question 5 Discussion
[Data Analysis]
A product goes viral on social media, creating high demand. Distribution channels are facing supply chain issues because the testing and training models that are used for sales forecasting have not encountered similar demand. Which of the following best describes this situation?
D imo, this feels more like skewing because the data distribution suddenly became unbalanced with that viral spike. The model likely was trained on more stable, evenly spread demand, so now that one type of data dominates, it’s not predicting well. Data drift usually implies a gradual change over time, but here it’s a sudden, extreme shift causing the supply chain issues.
B/C? The demand spike definitely changes the data pattern, pointing to data drift, but you could argue the model wasn’t sized for this extreme case either. Both seem plausible depending on perspective.
C imo, looks like the model’s sized wrong for peak demand, not just biased or drifting.
It’s A because the model was trained on past data that didn’t represent viral spikes, so its predictions are biased toward normal demand patterns it’s seen before.
This sounds like B because the model faces new data patterns it wasn’t trained on, which fits data drift causing forecast errors. Shah Y.
Maybe D? The product going viral sounds like the data or demand suddenly shifted, but the question says the models haven’t seen this kind of spike before. Wouldn’t this be more about the model not adapting to new patterns, like data drift (B)? I’m not sure what they mean exactly by "skewing" here—does it refer to distribution skew or something else? A bit unclear on that. Also, does the question imply the model is wrong because of biased training data (A) or just outdated data? Missing some detail on how the models were trained or updated.