Cyber Monday 2024! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions

Microsoft Exam MB-260 Topic 3 Question 26 Discussion

Actual exam question for Microsoft's MB-260 exam
Question #: 26
Topic #: 3
[All MB-260 Questions]

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 are implementing Microsoft Dynamics 365 Customer Insights as your company's Customer Data Platform.

The initial dataset tables contain contacts from Dynamics 365 Sales. eCommerce customers, and service management platform incidents.

In your first unification run, you set Dynamics 365 as the primary table but only see eCommerce profiles that were able to be matched with Dynamics 365 contacts.

You need to ensure that unmatched eCommerce customers are also added as a profile in Dynamics 365 Customer Insights.

Solution: Adjust the first condition in the matching rule with the lowest precision.

Does this meet the goal?

Show Suggested Answer Hide Answer
Suggested Answer: B

Contribute your Thoughts:

Stephane
5 months ago
I agree. Just adjusting one condition may not be enough to add all unmatched eCommerce customers as profiles.
upvoted 0 times
...
Haydee
5 months ago
Maybe we should reevaluate the matching rules and conditions to ensure we capture all eCommerce customers.
upvoted 0 times
...
Janella
5 months ago
I agree with User3. This solution may not meet the goal.
upvoted 0 times
...
Shannan
5 months ago
I believe the solution is not correct. We might have to try a different approach.
upvoted 0 times
...
Stephane
5 months ago
But will that really add unmatched eCommerce customers as profiles?
upvoted 0 times
...
Haydee
6 months ago
I think the solution is to adjust the first condition in the matching rule with the lowest precision.
upvoted 0 times
...
Thurman
6 months ago
That's a good point. It might cause more issues. I would say no.
upvoted 0 times
...
Gilma
7 months ago
But what if adjusting the precision messes up the matching for other profiles?
upvoted 0 times
...
Shasta
7 months ago
I think the solution should work, so I would say yes.
upvoted 0 times
Arlie
6 months ago
Agreed, the solution should work.
upvoted 0 times
...
Desiree
7 months ago
Yes
upvoted 0 times
...
...
Aretha
8 months ago
Hold up, guys. I think we need to take a step back and really think this through. If we're not careful, we could end up with a mess of duplicate profiles and incorrect data. Let's consider all the options before making a move.
upvoted 0 times
...
Melissa
8 months ago
Exactly, and you know what they say - 'garbage in, garbage out'. We don't want to end up with a bunch of messy, inaccurate data just to get those eCommerce profiles in there.
upvoted 0 times
...
Norah
8 months ago
Ugh, I hate these tricky data integration questions. They're always trying to trip you up. I say we just go for it and see what happens. What's the worst that could happen? Oh wait, don't answer that.
upvoted 0 times
...
Stefania
8 months ago
You know, I've had some experience with this kind of thing before. Lowering the precision on the matching rule could work, but it's also going to increase the likelihood of false positives. We need to weigh the potential benefits against the risks.
upvoted 0 times
...
Lajuana
8 months ago
Yeah, that sounds like a much better approach. I'm not a fan of just lowering the precision on the main matching rule. That seems like a band-aid solution that could cause more issues down the line.
upvoted 0 times
...
Theresia
8 months ago
Ooh, that's a good idea! We could create a secondary matching rule with lower precision just for the eCommerce data, so we don't compromise the accuracy of the Dynamics 365 matches. That way we can pull in those unmatched profiles without messing up the rest of the data.
upvoted 0 times
...
Leanora
8 months ago
Hmm, adjusting the matching rule with the lowest precision? That seems like a pretty risky move. I'm not sure if that's going to give us the results we're looking for. We need to be really careful with how we handle that data unification.
upvoted 0 times
Herschel
7 months ago
That sounds like a more cautious approach.
upvoted 0 times
...
An
7 months ago
Perhaps we can review the matching rules more thoroughly.
upvoted 0 times
...
Kasandra
7 months ago
What do you suggest we do instead?
upvoted 0 times
...
Leanora
7 months ago
Maybe we should explore other options.
upvoted 0 times
...
Gerald
7 months ago
I agree, it does seem risky.
upvoted 0 times
...
Caitlin
7 months ago
No
upvoted 0 times
...
Margart
8 months ago
Yes
upvoted 0 times
...
...
Carmelina
8 months ago
Hmm, I see what they're going for, but I agree with the others. Lowering the precision could create more problems than it solves. Maybe we should look at adding a new matching rule specifically for the unmatched eCommerce customers instead?
upvoted 0 times
...
Minna
8 months ago
Yeah, I'm not sure about that either. Lowering the precision of the matching rule seems counterintuitive. Wouldn't that just lead to more false positives and potentially merge profiles that shouldn't be merged?
upvoted 0 times
...
Juan
8 months ago
Wait, so we need to ensure that unmatched eCommerce customers are also added as a profile in Dynamics 365 Customer Insights? I'm not sure adjusting the matching rule with the lowest precision is the way to go. Wouldn't that just reduce the accuracy of the matches we do have?
upvoted 0 times
...

Save Cancel