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Workday Prism Analytics Exam - Topic 3 Question 3 Discussion

Actual exam question for Workday's Workday Prism Analytics exam
Question #: 3
Topic #: 3
[All Workday Prism Analytics Questions]

[Data Prep and Transformation]

When joining datasets, what items must match?

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Suggested Answer: A

by Yuki at Jun 13, 2025, 07:11 PM

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Wilda
5 months ago
Not sure about that, can you really join without matching detail levels?
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Kris
5 months ago
Totally agree, matching field types is crucial!
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Catarina
5 months ago
I think it's more about the field names, right?
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Latricia
6 months ago
Wait, does the number of rows even matter?
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Tamala
6 months ago
Field types definitely need to match!
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Garry
6 months ago
I definitely remember that the field types must match, but I’m unsure if the number of rows matters in this context.
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Rikki
6 months ago
I feel like the level of detail in each dataset could also play a role, but I’m not confident about that.
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Katina
7 months ago
I remember practicing a question where it was important for the field names to match, but I can't recall if that was the main focus here.
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An
7 months ago
I think the field types for the Match Row fields need to match, but I'm not entirely sure if that's the only requirement.
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Krissy
7 months ago
Okay, I've got a strategy for this. The question is asking specifically about what "must match" when joining datasets, so the field types seem like the most relevant factor. I'll go with option A.
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Rikki
7 months ago
Wait, is it the level of detail in each dataset? I feel like that could also be important when joining data. I'm a little confused on the best way to approach this question.
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Mirta
7 months ago
The field names for the Match Row fields need to match, right? That seems like the most logical answer to me. I'm pretty confident that's the right approach.
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Estrella
8 months ago
Hmm, I'm a bit unsure on this one. I know joining datasets is important, but I can't quite remember all the specific requirements. I'll have to think this through carefully.
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Miesha
8 months ago
I think the key here is that the field types need to match between the datasets being joined. The question is specifically asking about what "must match" when joining, so I'll go with option A.
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Melita
10 months ago
D sounds right to me. The field names need to be the same, or else how would the system know what to match?
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Sylvie
9 months ago
Yes, that's correct. The field names are crucial for matching datasets.
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Allene
9 months ago
I agree, the field names need to match for the system to know what to join on.
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Myra
10 months ago
Haha, imagine if the number of rows had to match. That would be like trying to fit a square peg in a round hole!
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Reuben
10 months ago
D) The field names for the Match Row fields.
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Cammy
10 months ago
A) The field types for the Match Row fields.
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Jackie
11 months ago
I think it's C. The level of detail in each dataset needs to be the same, otherwise you'll end up with a mess.
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Tamala
10 months ago
C) The level of detail in each dataset.
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Pura
10 months ago
B) The number of rows in each dataset.
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Douglass
10 months ago
A) The field types for the Match Row fields.
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Brock
11 months ago
The field types for the Match Row fields have to match, duh. How else would you join the data properly?
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Louvenia
10 months ago
Exactly, matching field types is crucial for a successful data join.
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Sabina
10 months ago
D) The field names for the Match Row fields.
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Shawn
10 months ago
D) The field names for the Match Row fields.
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Gracia
10 months ago
A) The field types for the Match Row fields.
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Freeman
11 months ago
A) The field types for the Match Row fields.
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Tasia
11 months ago
I believe the field types for the Match Row fields must also match for successful dataset joining.
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Avery
11 months ago
I agree with Blondell, the field names need to match for joining datasets.
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Blondell
11 months ago
I think the field names for the Match Row fields must match.
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