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, 06:03 AM

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Jaime

2 days ago

Totally agree, model planning is key!

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Ty

8 days ago

It's definitely model planning where techniques are chosen.

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Dean

14 days ago

The discovery phase makes sense to me because it involves understanding the data and the business goals, which directly influences the techniques we choose.

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Leonor

19 days ago

I feel like it could also be during data preparation since that's when we get the datasets ready, but I lean towards discovery based on what we discussed in class.

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Cristen

24 days ago

I remember a practice question that emphasized the importance of the discovery phase for identifying models. That might be the right answer here.

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Estrella

1 month ago

I think the analytical techniques are determined during the model planning stage, but I'm not entirely sure.

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Phyliss

1 month ago

I'm feeling a bit lost on this one. The question is asking about when analytical techniques are determined, but the answer choices don't seem to map directly to the lifecycle stages. I may need to review my notes again to make sure I understand this properly.

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Polly

1 month ago

Okay, let me walk through this step-by-step. In the data science lifecycle, the Model planning stage is about defining the project goals and hypotheses. The Model building stage is where we actually select the analytical techniques to use. So I'm pretty confident the answer is B here.

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Stephaine

1 month ago

This seems like a straightforward question about the data science lifecycle. I think the answer is B - Model building, since that's where we'd determine the appropriate analytical techniques to apply.

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Delila

1 month ago

Hmm, I'm a bit unsure on this one. I was thinking it might be A - Model planning, since that's when we'd plan out the analysis approach. But B - Model building also makes sense. I'll have to think this through carefully.

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Carma

1 month ago

I'm pretty confident this is the Response Time Composition Chart option. That should give me a quick breakdown of where the performance issues are coming from.

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Royce

1 year 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

11 months ago

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

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Desmond

11 months ago

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

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Annett

11 months ago

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

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Florinda

12 months ago

D) Discovery

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Nicolette

12 months ago

C) Data preparation

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Carin

12 months ago

B) Model building

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Lynelle

12 months ago

A) Model planning

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Vesta

1 year 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

1 year 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

1 year 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

11 months ago

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

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Darci

11 months ago

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

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Monte

11 months ago

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

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Carmela

12 months ago

User 1: Model building is where the magic happens!

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Nobuko

1 year 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

1 year 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

1 year 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

12 months ago

C) Data preparation

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Katie

1 year ago

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

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Wade

1 year ago

A) Model planning

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Rochell

1 year ago

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

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France

1 year 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

1 year 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

1 year 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

1 year 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

1 year ago

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

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Teresita

1 year 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

12 months ago

D) Discovery

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Carmela

12 months ago

C) Data preparation

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Rosenda

12 months ago

B) Model building

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Marge

12 months ago

A) Model planning

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Anisha

12 months ago

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

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Wayne

12 months ago

D) Discovery

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Blair

1 year ago

B) Model building

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Elena

1 year ago

C) Data preparation

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Elvis

1 year ago

A) Model planning

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Roy

1 year ago

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

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Fannie

1 year ago

D) Discovery

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Isidra

1 year ago

C) Data preparation

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Margot

1 year ago

B) Model building

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Buck

1 year ago

A) Model planning

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Blossom

1 year 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

1 year 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

1 year 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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