CompTIA DA0-001 Exam - Topic 4 Question 67 Discussion

Actual exam question for CompTIA's DA0-001 exam

Question #: 67
Topic #: 4

Which option best concepts should be applied if a data set with 40 fields needs to be pared down to 20 fields and contains similar data across multiple fields?

BConsolidation

CCompliance

DStandardization

ADuplication

Show Suggested Answer

Suggested Answer: B

Consolidation is the process of combining multiple elements into a single, more effective or coherent whole. In the context of data analytics, consolidation would involve merging similar fields to reduce the overall number of fields in a dataset. This is particularly useful when a dataset contains redundant or similar data across multiple fields, as it helps to simplify the data structure and improve efficiency. Techniques such as dimensionality reduction are often applied to achieve this, where the goal is to retain the most informative and representative features of the data while reducing the number of total features.

Applied Dimensionality Reduction --- 3 Techniques using Python1.

Seven Techniques for Data Dimensionality Reduction2.

Best practices when working with datasets3.

Effectively Handling Large Datasets4.

by Sarina at Jan 23, 2026, 07:12 AM

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Kayleigh

1 day ago

Haha, this question is a piece of cake! Just throw some machine learning magic at it and call it a day.

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Tresa

7 days ago

Hmm, I'd probably try to identify redundant fields and combine them using techniques like data aggregation or dimensionality reduction.

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Reita

12 days ago

I'd say feature selection methods like correlation-based or wrapper-based selection would be the way to go.

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Vince

17 days ago

Definitely go with data reduction techniques like principal component analysis or factor analysis.

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Emily

22 days ago

This reminds me of a similar practice question where we had to use decision trees to determine feature importance. That might be relevant here too.

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Dominque

27 days ago

I feel like we should consider correlation analysis to identify which fields are redundant, but I can't recall the exact steps.

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Paulina

2 months ago

I remember practicing a question about dimensionality reduction, maybe PCA could help here?

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Zana

2 months ago

I think we might need to look at feature selection techniques, but I'm not entirely sure which ones would be best for this scenario.

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Zack

2 months ago

Whew, 40 fields to 20 - that's a lot of paring down. I'd start by talking to the stakeholders to understand the key use cases and priorities.

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Krystina

2 months ago

Sounds like a good opportunity to use some feature selection techniques. I'd look into methods like recursive feature elimination or LASSO regression.

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