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CompTIA DY0-001 Exam - Topic 4 Question 13 Discussion

Actual exam question for CompTIA's DY0-001 exam
Question #: 13
Topic #: 4
[All DY0-001 Questions]

A data scientist is standardizing a large data set that contains website addresses. A specific string inside some of the web addresses needs to be extracted. Which of the following is the best method for extracting the desired string from the text data?

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Suggested Answer: A

by Heidy at Nov 22, 2025, 11:59 AM

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Janna
22 hours ago
Regular expressions are perfect for this!
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Lajuana
6 days ago
Option A all the way. Regular expressions are the text-wrangling superpower you need to tame those website addresses.
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Gerri
11 days ago
Haha, "large language model" - that's like using a sledgehammer to crack a nut! Regular expressions are the surgical tool you need for this job.
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Maryann
16 days ago
Regular expressions are the clear choice. They're powerful, flexible, and perfect for this kind of targeted string extraction.
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Yuonne
22 days ago
I'd go with option A. Regular expressions are the Swiss Army knife of text processing - they can handle just about any extraction task.
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Raymon
27 days ago
Large language models seem powerful, but I doubt they are the best fit for just extracting a specific string from a URL. Regular expressions seem more straightforward.
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Blossom
1 month ago
I feel like I’ve seen a similar question before, and I think find and replace could work, but it might not be as flexible as regex for this task.
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Ernie
1 month ago
I'm not entirely sure, but I remember practicing with named-entity recognition for extracting information. It seems more suited for structured data though.
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Tiera
1 month ago
I think regular expressions might be the best choice here since they are specifically designed for pattern matching in strings.
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Fredric
2 months ago
I'm a bit confused by this question. I know regular expressions can be powerful, but I'm not sure if they're the best approach compared to the other options. Maybe I should research named-entity recognition or large language models a bit more before deciding.
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Scarlet
2 months ago
Regular expressions are definitely the way to go here. I've used them before for text extraction tasks, and I'm confident I can write a regex that will reliably pull out the desired string from the web addresses.
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Jade
2 months ago
Hmm, this is a tricky one. I think I'd start by trying a simple find and replace, but that might not be robust enough for a large data set. Regular expressions could be the way to go, but I'd need to make sure I understand the syntax well.
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Alexia
2 months ago
I think A) Regular expressions is the best choice. It's precise for text extraction.
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Belen
2 months ago
Regular expressions are definitely the way to go here. They're like a secret language for text manipulation!
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Lili
3 months ago
C) Large language model is overkill for just extracting strings.
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Leota
3 months ago
I'm a bit unsure about this one. I know regular expressions can be powerful, but I'm not sure if they're the best method compared to the other options. Maybe I should consider named-entity recognition or a language model as well.
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Trinidad
3 months ago
Regular expressions seem like the best approach here. I'm pretty confident I can use a well-crafted regex to extract the specific string from the web addresses.
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Helene
2 months ago
Definitely! It can handle complex patterns.
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Abel
3 months ago
I agree, regex is powerful for this.
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