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Big data

Total questions: 15

Worksheet time: 8mins

Name
Class
Date
1.

What is big data?

a)

a. Data with a limited number of variables

b)

b. Data with a limited volume

c)

c. Data with a large volume, variety, and velocity

d)

d. Data in a structured format only

2.

What is the primary goal of analyzing big data?

a)

a. To identify data quality issues

b)

b. To predict future trends and behavior

c)

c. To collect as much data as possible

d)

d. To control the data analysis process

3.

Which of the following can be a potential benefit of big data to businesses?

a)

a. Improved data quality

b)

b. Increased security and privacy

c)

c. Better decision-making based on insights

d)

d. Reduced need for data storage

4.

What is a possible drawback of big data analysis?

a)

a. Improved operational efficiency

b)

b. Reduced risk of cyber-attacks

c)

c. Ethical concerns

d)

d. Higher accuracy of data analysis

5.

Which of the following is an example of big data?

a)

a. A spreadsheet with 100 rows and 10 columns

b)

b. A database with 1,000 records

c)

c. A dataset with millions of rows and columns

d)

d. A document with text and images

6.

What is a potential solution to the quality concerns associated with big data?

a)

a. Reducing the amount of data collected

b)

b. Implementing data quality controls and processes

c)

c. Ignoring data quality issues

d)

d. Increasing the amount of data collected

7.

What is the main source of big data?

a)

a. Surveys and questionnaires

b)

b. Social media platforms and online transactions

c)

c. Government records and databases

d)

d. Industry reports and news articles

8.

What is the meaning of the term 'data velocity' in big data?

a)

a. The size of the data being analyzed

b)

b. The variety of the data being analyzed

c)

c. The speed at which data is generated and processed

d)

d. The complexity of the data being analyzed

9.

What are the three Vs used to describe big data?

a)

a. Veracity, Validation, and Variety

b)

b. Velocity, Volume, and Variety

c)

c. Volume, Validation, and Vulnerability

d)

d. Velocity, Veracity, and Visibility

10.

What is the difference between structured and unstructured data?

a)

a. Structured data is manually entered while unstructured data is automatically generated.

b)

b. Structured data is organized in a specific format while unstructured data is not.

c)

c. Structured data is big data, while unstructured data is small data.

d)

d. Structured data is easy to analyze, while unstructured data is not.

11.

Which of the following is a big data tool used for distributed storage and processing?

a)

a. Hadoop

b)

b. MySQL

c)

c. SQL Server

d)

d. Oracle

12.

What is the purpose of data mining in big data?

a)

a. To design databases for storing big data

b)

b. To identify patterns and relationships in large datasets

c)

c. To control access to big data

d)

d. To securely transfer big data across networks

13.

What is the role of a data scientist in big data analysis?

a)

a. To design and develop big data solutions

b)

b. To analyze and interpret big data

c)

c. To ensure the security and privacy of big data

d)

d. To manage and maintain big data infrastructure

14.

What is predictive analytics in big data?

a)

a. Using historical data to predict future trends and behavior

b)

b. Analyzing real-time data to make immediate decisions

c)

c. Collecting data to identify patterns and relationships

d)

d. Using machine learning algorithms to automate data analysis

15.

What is the challenge associated with big data in terms of privacy and security?

a)

a. The risk of data breaches and cyber attacks

b)

b. The complexity of analyzing large datasets

c)

c. The difficulty of collecting data from different sources

d)

d. The lack of tools and technology to automate data analysis