MENU
[Data Prep and Transformation]
When joining datasets, what items must match?
Suggested Answer: A
Get Premium Workday Prism Analytics Questions
as Interactive Web-Based Practice Test or PDF
Real Exam Format
Detailed Explanations
Instant Access
Get Your Practice Test
33 comments · newest first
WI
Wilda
10 months ago
Not sure about that, can you really join without matching detail levels?
KR
Kris
10 months ago
Totally agree, matching field types is crucial!
CA
Catarina
10 months ago
I think it's more about the field names, right?
LA
Latricia
10 months ago
Wait, does the number of rows even matter?
TA
Tamala
10 months ago
Field types definitely need to match!
GA
Garry
11 months ago
I definitely remember that the field types must match, but I’m unsure if the number of rows matters in this context.
RI
Rikki
11 months ago
I feel like the level of detail in each dataset could also play a role, but I’m not confident about that.
KA
Katina
11 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.
AN
An
11 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.
KR
Krissy
12 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.
RI
Rikki
12 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.
MI
Mirta
12 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.
ES
Estrella
1 year 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.
MI
Miesha
1 year 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.
ME
Melita
1 year ago
D sounds right to me. The field names need to be the same, or else how would the system know what to match?
SY
Sylvie
1 year ago
Yes, that's correct. The field names are crucial for matching datasets.
AL
Allene
1 year ago
I agree, the field names need to match for the system to know what to join on.
MY
Myra
1 year 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!
RE
Reuben
1 year ago
D) The field names for the Match Row fields.
CA
Cammy
1 year ago
A) The field types for the Match Row fields.
JA
Jackie
1 year 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.
TA
Tamala
1 year ago
C) The level of detail in each dataset.
PU
Pura
1 year ago
B) The number of rows in each dataset.
DO
Douglass
1 year ago
A) The field types for the Match Row fields.
BR
Brock
1 year ago
The field types for the Match Row fields have to match, duh. How else would you join the data properly?
LO
Louvenia
1 year ago
Exactly, matching field types is crucial for a successful data join.
SA
Sabina
1 year ago
D) The field names for the Match Row fields.
SH
Shawn
1 year ago
D) The field names for the Match Row fields.
GR
Gracia
1 year ago
A) The field types for the Match Row fields.
FR
Freeman
1 year ago
A) The field types for the Match Row fields.
TA
Tasia
1 year ago
I believe the field types for the Match Row fields must also match for successful dataset joining.
AV
Avery
1 year ago
I agree with Blondell, the field names need to match for joining datasets.
BL
Blondell
1 year ago
I think the field names for the Match Row fields must match.