Independence Day Deal! Unlock 25% OFF Today – Limited-Time Offer - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions

IAPP Exam CIPM Topic 9 Question 45 Discussion

Actual exam question for IAPP's CIPM exam
Question #: 45
Topic #: 9
[All CIPM Questions]

What are you doing if you succumb to "overgeneralization" when analyzing data from metrics?

Show Suggested Answer Hide Answer
Suggested Answer: D

The first step to mitigate further risks when a systems audit uncovers a shared drive folder containing sensitive employee data with no access controls is to restrict access to the folder. This can be done by implementing appropriate access controls, such as user authentication, role-based access, and permissions, to ensure that only authorized individuals can view and access the sensitive data.


https://www.sans.org/cyber-security-summit/archives/file/summit-archive-1492158151.pdf

https://www.itgovernance.co.uk/blog/5-reasons-why-employees-dont-report-data-breaches/

https://www.ncsc.gov.uk/guidance/report-cyber-incident

Contribute your Thoughts:

Malcolm
1 months ago
I'm surprised the answer isn't 'E) All of the above'. That's usually the case with these tricky exam questions!
upvoted 0 times
Willard
2 days ago
D) Trying to use several measurements to gauge one aspect of a program.
upvoted 0 times
...
Raymon
3 days ago
C) Using limited data in an attempt to support broad conclusions.
upvoted 0 times
...
Merilyn
20 days ago
A) Using data that is too broad to capture specific meanings.
upvoted 0 times
...
...
Ellen
2 months ago
Hah, I almost picked B. 'Possessing too many types of data' - that's a new one! Gotta watch out for that data overload.
upvoted 0 times
Tawna
11 days ago
Yeah, it's important to strike a balance and not go to extremes with data analysis.
upvoted 0 times
...
Eliz
21 days ago
C) Using limited data in an attempt to support broad conclusions.
upvoted 0 times
...
Dominic
27 days ago
A) Using data that is too broad to capture specific meanings.
upvoted 0 times
...
...
Lemuel
2 months ago
I was gonna go with D, but now I'm not so sure. Overgeneralization can definitely happen when you try to measure too many things at once.
upvoted 0 times
Jeniffer
13 days ago
I agree, it's important to have a balance and not go to extremes.
upvoted 0 times
...
Karl
17 days ago
C) Using limited data in an attempt to support broad conclusions.
upvoted 0 times
...
Latosha
27 days ago
A) Using data that is too broad to capture specific meanings.
upvoted 0 times
...
...
Shawnda
2 months ago
Hmm, I was leaning towards A, but C makes a lot of sense too. Gotta be careful not to draw big conclusions from a small data set.
upvoted 0 times
Blossom
6 days ago
User 4: It's definitely crucial to be cautious when drawing conclusions from a small data set. Both A and C highlight the risks of overgeneralization.
upvoted 0 times
...
Stefan
9 days ago
User 3: I was also thinking A, but after hearing your points, C seems like a valid choice too.
upvoted 0 times
...
Evan
13 days ago
User 2: I agree with you, Evan. Using limited data to support broad conclusions can lead to overgeneralization.
upvoted 0 times
...
Nakita
17 days ago
User 1: I think A is the right answer. It's important to avoid using data that is too broad.
upvoted 0 times
...
Franchesca
19 days ago
D) Trying to use several measurements to gauge one aspect of a program.
upvoted 0 times
...
Mireya
28 days ago
Yeah, it's important to strike a balance between the two.
upvoted 0 times
...
Roselle
1 months ago
C) Using limited data in an attempt to support broad conclusions.
upvoted 0 times
...
Antonio
2 months ago
A) Using data that is too broad to capture specific meanings.
upvoted 0 times
...
...
Dell
2 months ago
I think C is the correct answer. Overgeneralizing from limited data is a common mistake in data analysis.
upvoted 0 times
Lonny
19 days ago
Using too little data can definitely skew our analysis results.
upvoted 0 times
...
Han
24 days ago
I think C is the correct answer too. We need to be cautious of overgeneralizing.
upvoted 0 times
...
Rosalyn
2 months ago
It's important to ensure we have enough data to draw meaningful insights.
upvoted 0 times
...
Narcisa
2 months ago
I agree, using limited data to support broad conclusions can lead to inaccurate analysis.
upvoted 0 times
...
...
Callie
3 months ago
I believe option C is the correct answer. Using limited data can lead to inaccurate conclusions.
upvoted 0 times
...
Paris
3 months ago
I agree with Alysa. It's important to avoid overgeneralization and make sure our data is specific enough.
upvoted 0 times
...
Alysa
3 months ago
I think if you succumb to overgeneralization, you're using limited data to support broad conclusions.
upvoted 0 times
...

Save Cancel
az-700  pass4success  az-104  200-301  200-201  cissp  350-401  350-201  350-501  350-601  350-801  350-901  az-720  az-305  pl-300  

Warning: Cannot modify header information - headers already sent by (output started at /pass.php:70) in /pass.php on line 77