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What are two potential reasons for performance issues (when loading a dashboard) when using the CRM data stream type?
Suggested Answer: D
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31 comments · newest first
GE
Geraldo
11 months ago
Totally agree with B, too many daily rows can be a nightmare!
SA
Salley
11 months ago
Wait, is it really D? I thought data was stored differently.
LA
Lashonda
12 months ago
C makes sense, calculated measurements can be a hassle.
AR
Arlette
12 months ago
A seems off, I don't think they create automatically.
AN
Antonio
1 year ago
Definitely B, pacing can slow things down a lot.
CR
Cristal
1 year ago
I’m a bit confused about option A. I don’t recall if the automatic creation of 'CRM - Opportunity' impacts loading times, but it seems possible.
OR
Oren
1 year ago
I practiced a similar question, and I think the workspace level storage mentioned in option D might also contribute to performance issues.
LI
Linsey
1 year ago
I'm not entirely sure, but I feel like option C could be a factor too. If all measurements are calculated, that might slow things down.
LE
Letha
1 year ago
I think one reason could be related to pacing, like option B. I remember something about daily rows affecting performance.
SH
Shaquana
1 year ago
Hmm, I'm not sure about the workspace-level data storage. Does that mean the data is less accessible or optimized for dashboard loading? I'll have to think about that one.
RO
Rose
1 year ago
And the fact that all the measurements are calculated rather than mapped could also be a factor. That extra processing might be causing performance problems when loading the dashboard.
TR
Tracey
1 year ago
Ah, I think I know one of the reasons - the pacing of the data creation. If it's generating daily rows for every lead and opportunity, that could really slow things down, especially for large datasets.
RE
Regenia
1 year ago
Okay, let's see. I'm guessing it has something to do with the way the data is structured or processed. Maybe the automatic creation of the 'CRM - Opportunity' data stream is causing issues?
FR
Francene
1 year ago
Hmm, this looks like it could be a tricky one. I'll need to think carefully about the potential reasons for performance issues with the CRM data stream type.
AL
Aleta
1 year ago
Hmm, I'm a bit unsure about this one. The options seem to be focused on different aspects of communication, but I'm not sure which one specifically indicates the behavioral tier. I'll have to think this through carefully.
LA
Lashon
1 year ago
Wait, so the CRM data stream is creating a row for every lead and opportunity, daily? That's like a million rows a day! No wonder the dashboard is sluggish - the poor server must be gasping for air!
RO
Robt
1 year ago
C) No mappable measurements - all measurements are calculated
PE
Pedro
1 year ago
B) Pacing - daily rows are being created for every lead and opportunity keys
TY
Ty
1 year ago
A) When a data stream type ''CRM - Leads' is created, another complementary 'CRM - Opportunity' is created automatically.
NI
Nicolette
1 year ago
D) The data is stored at the workspace level - oh, that's a good one. If the data is not partitioned or optimized for querying, that could definitely slow things down. Workspace-level storage is probably not the best choice for a CRM data stream.
ME
Melvin
1 year ago
I'm surprised option A) is even an option. Creating a complementary data stream type automatically? That sounds like a recipe for disaster, not a reason for performance issues!
FR
Francesco
2 years ago
C) No mappable measurements - all measurements are calculated - that's an interesting point. If there are no pre-calculated metrics and everything needs to be computed on the fly, that could definitely impact performance.
GL
Glendora
1 year ago
C) No mappable measurements - all measurements are calculated - that's an interesting point. If there are no pre-calculated metrics and everything needs to be computed on the fly, that could definitely impact performance.
CA
Carey
1 year ago
B) Pacing - daily rows are being created for every lead and opportunity keys
SH
Sheridan
1 year ago
A) When a data stream type 'CRM - Leads' is created, another complementary 'CRM - Opportunity' is created automatically.
NE
Nelida
2 years ago
B) Pacing - daily rows are being created for every lead and opportunity keys - that seems like a reasonable explanation for performance issues. The constantly growing data volume could definitely slow down the dashboard loading.
ED
Edna
1 year ago
B) Pacing - daily rows are being created for every lead and opportunity keys - that seems like a reasonable explanation for performance issues.
LO
Lonny
2 years ago
A) When a data stream type 'CRM - Leads' is created, another complementary 'CRM - Opportunity' is created automatically.
TA
Tamra
2 years ago
I believe the data being stored at the workspace level could also contribute to performance issues.
RE
Reid
2 years ago
I agree with Nan. Pacing and no mappable measurements can definitely cause performance issues.
NA
Nan
2 years ago
I think the potential reasons could be pacing and no mappable measurements.