CompTIA Exam DA0-001 Topic 5 Question 39 Discussion

Actual exam question for CompTIA's DA0-001 exam

Question #: 39
Topic #: 5

Which of the following tools would be best to use to calculate the interquartile range, median, mean, and standard deviation of a column in a table that has 5.000.000 rows?

AMicrosoft Excel

CSnowflake

DSQL

Show Suggested Answer

Suggested Answer: A

by Tanja at Jul 17, 2024, 08:30 PM

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Hoa

27 days ago

This is a job for the R-pocalypse! Seriously, Excel would probably just throw in the towel and go on vacation if you asked it to handle 5 million rows. And Snowflake, bless its heart, is more of a data storage solution than a statistical workhorse. R, on the other hand, is like a data analysis superhero. Bring it on, 5 million rows!

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Daniel

1 months ago

R is the way to go here, no doubt. I mean, who wants to wait forever for Excel to crunch through 5 million rows? And Snowflake is great for warehousing, but not so much for hardcore number-crunching. Time to break out the R magic!

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Billye

14 days ago

SQL could work too, but R is definitely faster for this task.

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Edmond

16 days ago

I agree, Excel would take forever to process 5 million rows.

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Lavonne

22 days ago

R is definitely the best choice for handling that amount of data.

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Jani

1 months ago

I'm going with option B. R is specifically designed for this kind of heavy-duty data analysis. Excel might work, but it would be painfully slow. And Snowflake and SQL are more for data storage and querying, not advanced statistical computations.

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Blythe

1 months ago

B for sure. R is a power tool for statistical analysis, and it can handle huge datasets like no other. Excel would probably start smoking if you tried to run those calculations on 5 million rows!

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Mozell

2 days ago

D) SQL

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Denny

22 days ago

I agree, R is definitely the best choice for handling such a large dataset.

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Whitney

30 days ago

B) R

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Sheridan

2 months ago

I personally prefer using Microsoft Excel for these calculations as it is user-friendly and easy to use.

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Erinn

2 months ago

Hmm, I'd say R would be the way to go for crunching those big numbers. Excel might choke on a dataset that size, and Snowflake is more for warehousing than analysis, right? SQL could work, but R has those built-in stats functions that would make this a breeze.

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