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

Limited Time Offer

25%

Off

Get Premium DP-100 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Yolando

5 months ago

I'll double-check the requirements and the capabilities of the Join Data module to see if there are any potential limitations.

upvoted 0 times

...

Nadine

5 months ago

That's a good point, Nadine. We should make sure the solution covers all rows from both datasets before concluding it meets the goal.

upvoted 0 times

...

Nadine

5 months ago

But what if the Join Data module doesn't actually combine all rows from both input datasets? That could be a problem.

upvoted 0 times

...

Yolando

5 months ago

I agree with Nadine. Using the Join Data module seems like the right approach to achieve that.

upvoted 0 times

...

Nadine

5 months ago

I think the solution meets the goal because we need to combine both input datasets into one with the same columns and header row.

upvoted 0 times

...

Willard

5 months ago

But why complicate things when the Join Data module can do the job?

upvoted 0 times

...

Fatima

5 months ago

I'm not sure, I think we should explore other options before deciding.

upvoted 0 times

...

Cherelle

5 months ago

I agree with using the Join Data module seems like the right approach.

upvoted 0 times

...

Willard

5 months ago

Yes, that's exactly what the goal is asking for.

upvoted 0 times

...

Eve

6 months ago

But won't that create a dataset with columns and header row from both input datasets?

upvoted 0 times

...

Willard

6 months ago

I think the solution is to use the Join Data module.

upvoted 0 times

...

Jamey

7 months 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.

upvoted 0 times

...

Leontine

7 months 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.

upvoted 0 times

Levi

6 months ago

Yes, it should work

upvoted 0 times

...

Eden

6 months ago

Fingers crossed

upvoted 0 times

...

Maira

6 months ago

Hopefully it works

upvoted 0 times

...

Merissa

6 months ago

Let's give it a try

upvoted 0 times

...

Elmira

6 months ago

Me too

upvoted 0 times

...

Viola

6 months ago

I agree

upvoted 0 times

...

Cassie

6 months ago

upvoted 0 times

...

Stanton

7 months 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.

upvoted 0 times

...

Sylvie

7 months 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.

upvoted 0 times

...

Cordelia

7 months 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.

upvoted 0 times

...

Simona

7 months 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?

upvoted 0 times

Shannan

5 months ago

upvoted 0 times

...

Stefany

5 months ago

Yes

upvoted 0 times

...

Andree

7 months 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?

upvoted 0 times

...

Theresia

7 months 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.

upvoted 0 times

...

Teddy

7 months 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.

upvoted 0 times

...

Queen

7 months 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.

upvoted 0 times

...