Question 1

What is the goal of data analytics?

A) To collect and store data.

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B) To visualize data for entertainment.

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C) To turn data into actionable insights.

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D) To create complex data models.

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Question 2

Which phase of the CRISP-DM framework involves understanding the problem and defining project goals?

A) Data Understanding

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B) Data Preparation

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C) Business Understanding

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D) Evaluation

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Question 3

What is the purpose of a conceptual data model?

A) To represent data in a specific technology.

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B) To define data requirements.

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C) To communicate the overall design to stakeholders.

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D) To include data types, indexes, and constraints.

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Question 4

Which stage of the data lifecycle involves securely deleting data that is no longer needed?

A) Modeling data requirements

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B) Obtaining data

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C) Removing data

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D) Using data for making business decisions

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Question 5

In the CRISP-DM framework, which phase involves cleaning, transforming, and prepping the data for analysis?

A) Modeling

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B) Data Understanding

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C) Data Preparation

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D) Deployment

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Question 6

What is the purpose of a logical data model?

A) To communicate the overall design to stakeholders.

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B) To represent data in a specific technology

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C) To include data types, indexes, and constraints

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D) To describe data in terms of organizational data requirements.

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Question 7

Which stage in the data lifecycle involves acquiring data from various sources?

A) Recording data

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B) Identifying data sources

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C) Modeling data requirements

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D) Using data for making business decisions

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Question 8

What is the purpose of a physical data model?

A) To represent data in a specific technology

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B) To define data requirements.

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C) To communicate the overall design to stakeholders.

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D) To describe data in terms of organizational data requirements.

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Question 9

Which stage of the data lifecycle involves using data to make informed decisions and improve business operations?

A) Modeling data requirements

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B) Obtaining data

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C) Using data for making business decisions

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D) Data Understanding

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Question 10

What is a characteristic of the CRISP-DM framework?

A) It has only four phases

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B) It follows a strictly linear sequence of phases

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C) It cannot be adapted to suit specific project needs

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D) It includes a phase for data deletion

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Question 11

Which of the following is a characteristic of big data?

A) Data with low volume, velocity, and variety

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B) Data that can be easily processed using traditional techniques

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C) Data characterized by high volume, velocity, and variety

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D) Data that is only generated from business transactions

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Question 12

What is the purpose of prescriptive analytics?

A) To summarize and describe past data

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B) To forecast future events

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C) To recommend actions to take based on data analysis

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D) To identify patterns and trends in historical data

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Question 13

Which of the 5Vs of big data refers to the accuracy and trustworthiness of the data?

A) Volume

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B) Velocity

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C) Variety

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D) Veracity

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Question 14

What type of data analytics involves analyzing historical data to understand patterns and trends?

A) Descriptive analytics

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B) Predictive analytics

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C) Prescriptive analytics

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D) Veracity analytics

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Question 15

Which characteristic of big data deals with the potential insights that can be gained from the data?

A) Volume

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B) Value

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C) Variety

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D) Velocity

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Question 16

Which tool is an open-source data cleaning tool with a user-friendly interface?

A) Alteryx

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B) SSIS

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C) DataStage

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D) OpenRefine

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Question 17

Which technology is designed to handle large amounts of unstructured and semi-structured data?

A) SQL

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B) Oracle

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C) Cloud computing

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D) NoSQL

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Question 18

Which tool is known for its flexibility and is widely used for basic data visualizations?

A) Tableau

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B) Power BI

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C) Excel

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D) MicroStrategy

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Question 19

Which cloud computing platform offers services like Amazon RDS and Amazon Redshift for data storage and management?

A) AWS (Amazon Web Services)

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B) Azure (Microsoft Azure)

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C) Oracle Cloud

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D) Google Cloud Platform

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Question 20

Which tool is known for creating interactive and visually appealing dashboards and is developed by Microsoft?

A) Tableau

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B) Power BI

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C) Excel

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D) MicroStrategy

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Question 21

What is a common technique used in data science to transform and manipulate data into a structured format?

Data visualization

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Data mining

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Data warehousing

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Data wrangling

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Question 22

Which of the following is a benefit of using data visualization in data science?

Increasing data accessibility

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Decreasing data exploration

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Reducing data interpretation

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Making data more complex

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Question 23

In the context of data analytics, what does the acronym “CRISP” stand for?

Complex Regression and Information Search Protocol

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Cross-industry Resource for In-depth Statistical Planning

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Comprehensive Reporting of Information and Statistical Processes

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Cross-Industry Standard Process for Data Mining

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Question 24

Which stage of the data lifecycle involves cleaning, transforming, and prepping the data for analysis?

Deployment

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Data Preparation

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Modeling

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Data Understanding

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Question 25

Which of the following is an example of a descriptive analytics technique?

Summarizing sales trends

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Optimizing supply chain operations

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Recommending products to users

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Predicting customer churn

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Question 26

What type of data analysis is focused on forecasting future events based on historical data?

Predictive analytics

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Diagnostic analytics

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Prescriptive analytics

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Descriptive analytics

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Question 27

Which type of machine learning model is used for classification tasks where the outcome is discrete categories?

Principal Component Analysis

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Clustering

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Regression

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Decision Tree

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Question 28

In a linear regression model, what is the goal of the learning process?

Minimize the testing error

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Maximize the accuracy

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Minimize the number of features

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Minimize the training error

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Question 29

What is the primary purpose of using data visualization techniques in data science?

Enhancing data exploration

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Complicating the decision-making process

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Reducing data accessibility

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Making the data more complex

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Question 30

Which type of data visualization is best suited for comparing different categories of data?

Scatter plot

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Pie chart

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Bar chart

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Line chart

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Question 31

What is a key ethical consideration in data science?

Ensuring data accuracy and quality

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Using personal data without consent

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Focusing on maximizing profits

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Ignoring privacy concerns

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Question 32

Which principle emphasizes the need for transparency and accountability when using data for decision-making?

Data fragmentation

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Data monetization

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Data privacy

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Data governance

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