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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?

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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

by Markus at Mar 31, 2023, 02:31 PM

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Malcolm
3 months ago
I'm surprised the answer isn't 'E) All of the above'. That's usually the case with these tricky exam questions!
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Willard
2 months ago
D) Trying to use several measurements to gauge one aspect of a program.
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Raymon
2 months ago
C) Using limited data in an attempt to support broad conclusions.
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Merilyn
3 months ago
A) Using data that is too broad to capture specific meanings.
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Ellen
4 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.
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Tawna
2 months ago
Yeah, it's important to strike a balance and not go to extremes with data analysis.
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Eliz
3 months ago
C) Using limited data in an attempt to support broad conclusions.
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Dominic
3 months ago
A) Using data that is too broad to capture specific meanings.
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Lemuel
4 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.
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Jeniffer
2 months ago
I agree, it's important to have a balance and not go to extremes.
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Karl
2 months ago
C) Using limited data in an attempt to support broad conclusions.
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Latosha
3 months ago
A) Using data that is too broad to capture specific meanings.
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Shawnda
4 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.
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Blossom
2 months 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.
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Stefan
2 months ago
User 3: I was also thinking A, but after hearing your points, C seems like a valid choice too.
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Evan
2 months ago
User 2: I agree with you, Evan. Using limited data to support broad conclusions can lead to overgeneralization.
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Nakita
2 months ago
User 1: I think A is the right answer. It's important to avoid using data that is too broad.
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Franchesca
3 months ago
D) Trying to use several measurements to gauge one aspect of a program.
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Mireya
3 months ago
Yeah, it's important to strike a balance between the two.
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Roselle
3 months ago
C) Using limited data in an attempt to support broad conclusions.
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Antonio
3 months ago
A) Using data that is too broad to capture specific meanings.
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Dell
4 months ago
I think C is the correct answer. Overgeneralizing from limited data is a common mistake in data analysis.
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Lonny
3 months ago
Using too little data can definitely skew our analysis results.
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Han
3 months ago
I think C is the correct answer too. We need to be cautious of overgeneralizing.
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Rosalyn
4 months ago
It's important to ensure we have enough data to draw meaningful insights.
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Narcisa
4 months ago
I agree, using limited data to support broad conclusions can lead to inaccurate analysis.
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Callie
4 months ago
I believe option C is the correct answer. Using limited data can lead to inaccurate conclusions.
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Paris
5 months ago
I agree with Alysa. It's important to avoid overgeneralization and make sure our data is specific enough.
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Alysa
5 months ago
I think if you succumb to overgeneralization, you're using limited data to support broad conclusions.
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