Microsoft Exam DP-100 Topic 8 Question 99 Discussion

Actual exam question for Microsoft's DP-100 exam

Question #: 99
Topic #: 8

Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.

After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.

You use Azure Machine Learning designer to load the following datasets into an experiment:

You need to create a dataset that has the same columns and header row as the input datasets and contains all rows from both input datasets.

Solution: Use the Join Data module.

Does the solution meet the goal?

AYes

BNo

Show Suggested Answer

Suggested Answer: B

by Mirta at Apr 08, 2024, 07:43 AM

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Jamey

9 days ago

Hmm, I'm with you on the Join Data module, but I'm a little concerned about the 'not able to return to it' part. What if we miss something or need to double-check our work? Oh well, no use worrying about that now. Let's go with the Join Data solution and move on.

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Leontine

9 days ago

I think the solution provided is a good starting point, but I would want to verify that the resulting dataset truly meets the stated goals. Sometimes these Azure modules can be a bit tricky.

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Stanton

10 days ago

I agree, the Join Data module sounds like the way to go. It's a common data transformation technique, and it should give us the desired output. Plus, the question states that this is one of a series, so the solution is likely intended to be correct.

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Sylvie

11 days ago

Well, the instructions say that the solution might meet the stated goals, so I'm assuming the Join Data module is the correct approach here. It will combine the two input datasets into a single dataset with the same columns and headers.

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Cordelia

11 days ago

Ha, this question reminds me of that time I accidentally joined two datasets with completely different schemas. Ended up with a huge mess of data! Hopefully, the Join Data module is a bit more intelligent than my manual attempts.

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Simona

12 days ago

I'm a bit confused by the question. What exactly do they mean by 'same columns and header row'? Could the solution involve some data transformation or cleaning steps before joining the datasets?

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Andree

12 days ago

I'm not sure about this question. The solution seems straightforward, but I want to make sure I understand the context correctly. What do you all think?

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Theresia

13 days ago

Hmm, the solution seems logical, but I wonder if there are any other ways to accomplish the same goal. I'd want to explore all my options before selecting an answer.

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Teddy

15 days ago

The question seems straightforward, but I'm not sure if the provided solution is the best approach. I might consider using other data manipulation modules in Azure Machine Learning to achieve the desired outcome.

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Queen

17 days ago

I think this question is a bit tricky. The solution provided is not entirely clear to me. I would need to understand more about the Join Data module and how it works in this specific scenario.

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