Databricks Exam Databricks-Certified-Professional-Data-Scientist Topic 6 Question 72 Discussion

Actual exam question for Databricks's Databricks-Certified-Professional-Data-Scientist exam

Question #: 72
Topic #: 6

[All Databricks-Certified-Professional-Data-Scientist Questions]

In which lifecycle stage are appropriate analytical techniques determined?

AModel planning

BModel building

CData preparation

DDiscovery
In Phase 3, the data science team identifies candidate models to apply to the data for clustering, classifying, or finding relationships in the data depending on the goal of the project, It is during this phase that the team refers to the hypotheses developed in Phase 1, when they first became acquainted with the data and understanding the business problems or domain area. These hypotheses help the team frame the analytics to execute in Phase 4 and select the right methods to achieve its objectives.
Some of the activities to consider in this phase include the following: Assess the structure of the datasets. The structure of the datasets is one factor that dictates the tools and analytical techniques for the next phase. Depending on whether the team plans to analyze textual data or transactional data, for example, different tools and approaches are required.
Ensure that the analytical techniques enable the team to meet the business objectives and accept or reject the working hypotheses. Determine if the situation warrants a single model or a series of techniques as part of a larger analytic workflow. A few example models include association rules and logistic regression Other tools, such as Alpine Miner, enable users to set up a series of steps and analyses and can serve as a front-end user interface (Ul) for manipulating Big Data sources in PostgreSQL.

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Suggested Answer: A

by Lorean at Sep 18, 2024, 05:03 AM

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Royce

2 months ago

Wait, there's an 'Alpine Miner' involved? I'm sold! That's gotta be the answer. Who doesn't love a good miner?

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Vilma

10 days ago

Alpine Miner it is then! Let's lock in our answer.

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Desmond

11 days ago

I agree, Alpine Miner does sound intriguing. Let's go with that.

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Annett

15 days ago

Alpine Miner sounds interesting, I think it might be the answer.

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Florinda

20 days ago

D) Discovery

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Nicolette

26 days ago

C) Data preparation

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Carin

1 months ago

B) Model building

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Lynelle

1 months ago

A) Model planning

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Vesta

2 months ago

Ah, the age-old debate of which came first, the chicken or the egg? I mean, do we determine the analytics based on the data, or the data based on the analytics? This is deep, my friends.

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Avery

2 months ago

This question is making my head spin. I'm just going to go with my gut and say 'D) Discovery'. Sounds like the most logical choice to me.

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Denny

2 months ago

I'm a little confused - isn't Model building the stage where you actually choose and apply the analytical techniques? That's where the magic happens!

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Paulina

13 days ago

User 3: In Phase 3, the data science team identifies candidate models based on hypotheses from Phase 1.

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Darci

13 days ago

Monte: Oh, I see. So Model building is where you apply the chosen techniques.

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Monte

14 days ago

User 2: Actually, appropriate analytical techniques are determined in Model planning.

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Carmela

1 months ago

User 1: Model building is where the magic happens!

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Nobuko

2 months ago

Nah, I'm going with Discovery. That's where you really dive into the data and figure out what's going on. The analytical techniques flow from that understanding.

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Lindsey

2 months ago

I think this is a trick question. The answer is definitely Data preparation - you need to clean and transform your data before you can even start modeling, right?

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Georgene

2 months ago

Hmm, seems like the appropriate analytical techniques are determined during the Model planning stage. That makes sense, as you need to plan your approach before actually building the model.

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Trinidad

1 months ago

C) Data preparation

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Katie

1 months ago

Yes, that's correct. Model planning is where the appropriate analytical techniques are determined.

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Wade

2 months ago

A) Model planning

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Rochell

2 months ago

I believe Data preparation is also crucial in determining the appropriate analytical techniques.

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France

2 months ago

Wait, is this a trick question? I mean, shouldn't we be determining the analytical techniques throughout the entire lifecycle, not just in one specific phase?

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Janet

2 months ago

A: Exactly. It's important to assess the structure of the datasets and select the right methods to achieve the project's goals.

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Belen

2 months ago

B: That's right. The team needs to ensure that the analytical techniques chosen align with the business objectives and working hypotheses.

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Kris

2 months ago

A: No, it's not a trick question. In Phase 3, we determine the appropriate analytical techniques based on the hypotheses developed in Phase 1.

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Brandee

2 months ago

I agree with Zena, it's important to select the right methods to achieve the objectives.

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Teresita

3 months ago

Ha, this is a tricky one! It's like trying to choose the perfect tool for the job without even knowing what the job is. I'd say the discovery phase is key here.

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Lamonica

27 days ago

D) Discovery

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Carmela

28 days ago

C) Data preparation

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Rosenda

29 days ago

B) Model building

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Marge

1 months ago

A) Model planning

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Anisha

1 months ago

Yes, it's all about understanding the data and business problems before selecting the right methods.

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Wayne

1 months ago

D) Discovery

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Blair

1 months ago

B) Model building

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Elena

1 months ago

C) Data preparation

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Elvis

1 months ago

A) Model planning

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Roy

2 months ago

I agree, the discovery phase is crucial in determining the appropriate analytical techniques.

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Fannie

2 months ago

D) Discovery

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Isidra

2 months ago

C) Data preparation

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Margot

2 months ago

B) Model building

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Buck

2 months ago

A) Model planning

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Blossom

3 months ago

Hmm, I'm not sure I agree. I think the model planning phase is where you really decide on the right analytical techniques based on your hypotheses and business objectives.

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Wayne

3 months ago

I agree, the data preparation phase is crucial. It's like building a house - you need to have a solid foundation before you can start constructing the rest of the structure.

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Hassie

3 months ago

The data preparation phase is key in determining the appropriate analytical techniques. You can't just jump straight to the modeling without first understanding the data structure and addressing any quality or consistency issues.

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