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Talend-Core-Developer Exam - Topic 7 Question 12 Discussion

You need a list of all customers whose first name contains "Tom" and who are older than 18. Which processor should be used?
C) Filter
A) Join
B) Aggregate
D) Data sampling

Talend-Core-Developer Exam - Topic 7 Question 12 Discussion

Actual exam question for Talend's Talend-Core-Developer exam
Question #: 12
Topic #: 7
[All Talend-Core-Developer Questions]

You need a list of all customers whose first name contains "Tom" and who are older than 18. Which processor should be used?

Show Suggested Answer Hide Answer
Suggested Answer: C

Comprehensive and Detailed Explanation:

To filter customer records based on first name containing 'Tom' and age greater than 18, the Filter processor is the correct choice.

Filter (Option C) -- Correct Answer:

The Filter processor allows users to set conditional rules to extract only the required data.

Users can specify conditions such as:

first_name CONTAINS 'Tom'

AND

age > 18

This ensures that only relevant records are included in the output.

Why not other options?

Option A (Join): Used to combine data from multiple datasets based on a key field, not for filtering.

Option B (Aggregate): Used for summarizing data, such as calculating counts, sums, or averages.

Option D (Data Sampling): Used to select a random subset of data, not for filtering based on conditions.


Contribute your Thoughts:

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Marylin
9 months ago
Wait, why would you use Join? That seems unnecessary.
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Skye
9 months ago
I think Join could work too, but Filter is more straightforward.
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Sanda
9 months ago
Aggregate doesn’t fit here at all, right? Just checking!
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Owen
9 months ago
I’m surprised this isn’t a trick question! Filter seems too obvious.
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Kanisha
9 months ago
Definitely need to use Filter for this!
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Lyda
10 months ago
Data sampling doesn't seem right for this question, but I'm confused about whether to choose Filter or Aggregate.
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Quentin
10 months ago
I practiced a similar question last week, and I think we definitely need to apply some kind of filter here.
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Anglea
10 months ago
I'm not entirely sure, but I remember something about joins being used for combining data, not just filtering.
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Pedro
10 months ago
I think we need to filter the customers based on their first name and age, so maybe it's option C?
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Paulina
10 months ago
I think Filter is the way to go. We just need to apply the right conditions to the customer data to get the desired list.
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Elfrieda
11 months ago
Join seems like the obvious choice here. We need to combine the customer data with some age information to get the results we want.
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Rory
11 months ago
I'm a bit unsure about this one. I'm not sure if I should use Join or Filter. I'll have to think it through carefully.
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Lynsey
11 months ago
Hmm, this seems like a straightforward filtering task. I'd probably go with option C, Filter, to get the list of customers with first names containing "Tom" and who are over 18.
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Maile
11 months ago
I think Join could also work, as we need to combine data from different sources.
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Lashawn
1 year ago
D) Data sampling? Hmm, I don't think we need to sample the data here. We want the full list of matching cusShaniquaers.
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Verdell
11 months ago
D) Data sampling? Hmm, I don't think we need to sample the data here. We want the full list of matching customers.
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Billi
12 months ago
C) Filter
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Skye
1 year ago
I agree with Margurite, Filter seems like the right choice.
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Margurite
1 year ago
I think we should use Filter for this task.
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Layla
1 year ago
A) Join? Are we trying to combine cusShaniquaer data with another dataset? That's not what this question is asking.
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Dyan
11 months ago
C) Filter
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Deangelo
11 months ago
C) Filter
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Pedro
12 months ago
C) Filter
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Margarita
1 year ago
B) Aggregate? Really? What are we, counting the number of Shaniquas or something?
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Shaniqua
1 year ago
C) Filter is the correct answer here. We need to filter the cusShaniquaers whose first name contains 'Shaniqua' and who are older than 18.
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Mozell
1 year ago
A) Join
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