Which of the following is not a part of Data Science process?

Question

A) Discovery

B) Model Planning

C) Communication Building

D) Operationalize

Answer 1

The correct answer to the question “Which of the following is not a part of the Data Science process” is option ©. Communication Building. Because all the other process like Discovery (Data Discovery), Model Planning (Data Model Planning), Operationalize are all part of the Data Science processes. Whereas, Communication Building is not on the list of Data Science processes.

Enroll in a good Data Science course, if you are aspiring to become a qualified Data Scientist. And also, watch the following video on Data Science Career to get started.

Answer 2

Data science extracts meaning from data through a set of pipelines:

Discovery: Consider the objectives, analyze the data, and understand the issue.

Model configuration: It defines the algorithm and solves the issues in the model.

Mobilize: Uses the best possible models to apply the insight provided.

Although communication is not an important step in data science, it is crucial in communicating findings to stakeholders. Hence the answer is C.

Answer 3

A) In the first phase, the objectives of the project and related data sources are determined by data scientists. This phase is critical to ensure goals are clear and a proper understanding of the problem exists.

B) Here, in the second phase, the methods are chosen, and the roadmap for analysis is established by the data scientist. The techniques to be adopted for modeling and data requirement have to be decided to properly address the problem.

C) Communication Building: It is not a traditional phase of Data Science. Even though results need to be communicated, "Communication Building" is not a phase in and of itself.

D) Operationalize: It is when the model goes to production so that it could be utilized in the real world. It helps the model function on real-time data and to give constant insights.

Answer 4

A) In the first phase, the objectives of the project and related data sources are determined by data scientists. This phase is critical to ensure goals are clear and a proper understanding of the problem exists.

B) Here, in the second phase, the methods are chosen, and the roadmap for analysis is established by the data scientist. The techniques to be adopted for modeling and data requirement have to be decided to properly address the problem.

C) Communication Building: It is not a traditional phase of Data Science. Even though results need to be communicated, "Communication Building" is not a phase in and of itself.

D) Operationalize: It is when the model goes to production so that it could be utilized in the real world. It helps the model function on real-time data and to give constant insights.