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Huawei H13-711 Exam - Topic 1 Question 56 Discussion

What are the main features of big data analysis related technologies? (Multiple choices)
A) Machine learning, full features and B) Analysis of the relevance of events behind the data and C) Based on massive data
D) based on exact samples

Huawei H13-711 Exam - Topic 1 Question 56 Discussion

Actual exam question for Huawei's H13-711 exam
Question #: 56
Topic #: 1
[All H13-711 Questions]

What are the main features of big data analysis related technologies? (Multiple choices)

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Suggested Answer: A, B, C

by Willodean at Jul 31, 2022, 05:36 PM

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Franchesca
9 months ago
Totally agree with you, Elbert!
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Royce
9 months ago
Massive data is a must for big data analysis!
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Marti
9 months ago
Wait, based on exact samples? That doesn't sound right.
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Terrilyn
9 months ago
I think relevance analysis is super important too.
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Elbert
9 months ago
Machine learning is definitely a key feature!
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Jovita
10 months ago
Option D seems off to me; big data usually deals with large datasets rather than exact samples, right?
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Lucille
10 months ago
I think analyzing the relevance of events is important too, but I can't recall if that was specifically mentioned in our practice questions.
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Glynda
10 months ago
I'm not entirely sure, but I feel like machine learning is a big part of big data analysis. Maybe A is correct?
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Berry
10 months ago
I remember studying that big data is all about handling massive datasets, so I think option C is definitely a key feature.
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Raylene
10 months ago
Linear programming is definitely a constrained optimization technique, so I'm going to go with that answer. The key is finding the optimal solution while meeting certain constraints, which is what constrained optimization is all about.
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Santos
10 months ago
I feel pretty confident about this one. Configuration item associations are all about making connections between assets to improve management and visibility. Option B seems to capture that benefit the best.
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Wilburn
10 months ago
Okay, let me think this through. The load balancer is internal, so the VMs in the backend pool need to be in the same virtual network. Disassociating the public IP from VM2 should allow me to add it to the backend pool.
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