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Big Data Analytics MCQ
2023-06-03 23:34:10

Big Data Analytics MCQ

Multiple choice questions are types of questions where a variety of alternatives or response possibilities follow a question. The person who responds must choose an appropriate answer from the offered choices. Multiple-choice questions are frequently used and applied in educational situations to assess the student's comprehension, expertise, and understanding. They additionally work in standard tests, specialized exams, and various other forms of evaluations.

These questions are simple but require a strong foundation on the subject because these questions are not narrative. These include various options present in front of us to test our capabilities and knowledge on the subject. The options will be complex, and they may be twisted and puzzling, which might sound familiar, but they are not.

The person taking these tests must carefully select the options presented to score a good grade on these tests.

Big Data Analytics

The act of assessing and comprehending huge and elaborate information to find hidden patterns, connections, and other significant details that could be utilized for making more effective company choices is called big data analytics. To derive meaningful information from the quantity, speed, and variety of data associated with Big Data Analytics, advanced methods and tools like machine learning methods, data analysis, and information visualization are required. Big Data Analytics is implemented to find new possibilities, cutting expenditures while improving performance in general in a range of professions, including banking, healthcare, the retail sector, and telecommunication.

Analytics deals with a huge amount of data to work on; for instance, consider hospitals that have patient records that are huge and new data will be added daily. This may cause strain and burden on the staff working on the records of patients and sorting them accordingly. Here Big Data Analytics is used to manage the huge amount of data that can be organized and managed easily anytime.

Big data analytics have importance since it enables organizations to use existing data to find areas for development and management. Improved productivity leads to improved tasks, bigger earnings, and pleased consumers throughout all company sectors. Big data analytics makes it easier for companies to lower costs and develop more client-focused services and products.

Hadoop is a free and open-source platform for storing and analyzing enormous quantities of data that is distributed. The Apache Software Foundation created it, and it is built on the Google File System, which uses MapReduce programming architecture.

Multiple Choice Questions on Big Data Analytics

Hadoop was created for organising huge amounts of datathat can be identified by immense amount, speed, and diversity. Organisations utilise it to hold, process, & interpret large volumes of personal information inside an environment that utilises distributed computing.

Hadoop has two main components:

  1. HDFS (Hadoop Distributed File System) is a global directory system that offers reliable and accessible storage across huge data collections. Hadoop Distributed File Systemis intended to operate on standard hardware, therefore being inexpensive.
  2. MapReduce is a computer methodology for handling enormous amounts of data. MapReduce enables programmers to create applications that can handle huge amounts of information while running simultaneously on a collection of machines. Hadoop has increased in popularity because of its adaptability and capacity to handle large amounts of data. Adding additional nodes to the cluster is simple to accommodate growing data and processing demands. Hadoop also features reliability, meaningwork is immediately redirected to another node when any of the clusters fails.

Across various sectors, big data analytics provides discoveries and influencesdecision-making.

These are a few practical examples in which big data analysis is being used:

  1. Healthcare
  2. Finance
  3. Educational Institutions
  4. Manufacturing

Healthcare

The Healthcare industry plays an important role in storing and managing huge amounts of data. This must involve big data to organise the patient’s data because this helps them to manage the data. To analyse and produce proper outcomes, big data must be integrated.

Finance

This is also one of the primary industries where big data is used a lot in their daily tasks. Finance includes huge tasks like the expenditures, profits and losses, income, stocks, shares, and many more. To manage all this, big data is used in the finance market to improve the efficiency in data management and boost the productivity.

Educational Institutions

Educational institutions also use big data because they also deal with large data set.From the first day of the institution to the end day, every record must be stored, from student details to faculty details, their attendance reports, absent reports, and progress in academics.It also includes some finance for providing salaries and collecting fees.

Manufacturing

Manufacturing businesses also integrate big data into their routines to increase the sales and profit from their product. They use the systems to analyse the product growth and understand the current market trends frequently.Maintenance of the product, and efficiency of the product are managed here.

Let us have a look at the Multiple-choice questions which are asked in big data analytics (with answers):

1. What is the process of identifying patterns and obtaining insights from large datasets?

  1. Data mining
  2. Data warehousing
  3. Data cleansing
  4. Data integration

Answer: A) Data mining

2. Which of the following is a primary characteristic of Big Data?

  1. High velocity
  2. Structured data
  3. Low volume
  4. Easy to manage

Answer: A) High velocity

3. Which of the following is an instance of unstructured data?

  1. Spreadsheet data
  2. Sensor data
  3. Social media data
  4. Financial data

Answer: C) Social media data

4. Which of the following is aninstance of a Big Data Analytics tool?

  1. Microsoft Excel
  2. Tableau
  3. Adobe Photoshop
  4. Google Docs

Answer: B) Tableau

5. From the following options, which technologies are commonly used for Big Data Analytics?

  1. Hadoop
  2. MySQL
  3. MongoDB
  4. PHP

Answer: A) Hadoop

6. What is the main aim of Big Data Analytics?

  1. To store and process large amounts of data
  2. To identify patterns and extract insights from large datasets
  3. To make data available to users in real-time
  4. To improve data security and privacy

Answer: B) To identify patterns and extract insights from large datasets

7. Which of the following is a data storage system commonly used in Big Data Analytics?

  1. Cloud storage
  2. Network-attached storage
  3. Object storage
  4. All of the above

Answer: D) All of the above

8. From the following which is a method of processing data in parallel across multiple computers?

  1. MapReduce
  2. SQL
  3. Hadoop
  4. NoSQL

Answer: A) MapReduce

9. Which of the following is the most difficult challenge in Big Data Analytics?

  1. Data security
  2. Data integration
  3. Data Accuracy
  4. All of the above

Answer: D) All of the above

10. Which of the following is a process of analysing data using statistical models?

  1. Predictive analytics
  2. Prescriptive analytics
  3. Descriptive analytics
  4. All of the above

Answer: D) All of the above

11. Which of the following is areal-life example of a Big Data Analytics application in the financial industry?

  1. Fraud detection
  2. Customer relationship management
  3. Inventory management
  4. Supply chain management

Answer: A) Fraud detection

12. What is the technique of combining data from different sources called?

  1. Data mining
  2. Data integration
  3. Data warehousing
  4. Data transformation

Answer: B) Data integration

13. Whichof the following options is a technique for reducing the amount of data processed?

  1. Sampling
  2. Clustering
  3. Regression
  4. Classification

Answer: A) Sampling

14. Which from the following is an example of a Big Data Analytics application in the healthcare industry?

  1. Predictive maintenance of medical equipment
  2. Fraud detection in insurance claims
  3. Analysis of patient data to identify disease patterns
  4. Real-time monitoring of hospital operations

Answer: C) Analysis of patient data to identify disease patterns

15. From the given which one is a method of data analysis that uses machine learning algorithms?

  1. Predictive analytics
  2. Prescriptive analytics
  3. Descriptive analytics
  4. All of the above

Answer: D) All of the above

16. Which among the following is one of the type of data visualization used in Big Data Analytics?

  1. Bar chart
  2. Line graph
  3. Heat map
  4. All of the above

Answer: D) All of the above

17. Among the following what is that database management system used in Big Data Analytics?

  1. MySQL
  2. Oracle
  3. Hadoop
  4. SQL Server

Answer: C) Hadoop

18. What are the types of Big Data?

  1. Structured
  2. Unstructured
  3. Semi-structured
  4. Hybrid
  5. All of the above

Answer: E) All of the above

19. What are the tools used in Analysing Big Data?

  1. Cassandra
  2. MySQL
  3. Amazon AWS
  4. Avalon

Answer: A) Cassandra

20. The data which is worked in Big Data is?

  1. Meta Bytes
  2. Giga Bytes
  3. Kilo Bytes
  4. Peta Bytes

Answer: D) Peta Bytes

21. In which language is Hadoop written?

  1. C
  2. Python
  3. Java
  4. Ruby

Answer: B) Python

22. Whatcan be generally used to generate big data?

  1. Data warehouse
  2. SQL
  3. Panda
  4. None

Answer: A) Data warehouse

23. Which of the following allows Job Control in Hadoop?

  1. Mapper class
  2. Task class
  3. Job class
  4. All of the above

Answer: C) Job class

24. The time horizon in data warehousing is?

  1. 3 to 4 years
  2. 4 to 7 years
  3. 1 year
  4. 10 years

Answer: A) 3 to 4 years

25. MapReduce jobs are written in which language?

  1. Java
  2. Python
  3. HTML
  4. Both A and B
  5. Both B and C

Answer: D) Both A and B

26. What are the CAP capabilities?

  1. Consistency
  2. Availability
  3. Partition
  4. All the above

Answer: D) All the above

27. Hadoop can support which of the CAP capabilities?

  1. C,A
  2. A,P
  3. C,P
  4. A,P

Answer: B) A,P

28. What is the library used in MapReduce Code?

  1. X unit
  2. Y unit
  3. MR unit
  4. J unit

Answer: C) MR unit

29. What is the type of HDFS file?

  1. Read only
  2. Write only
  3. Read and write
  4. Append only

Answer: D) Append only

30. What is the full form of HDFS?

  1. Hadoop Development File System
  2. Hadoop Distributed File System
  3. Hadoop Database File System
  4. Hadoop Design File System

Answer: B) Hadoop Distributed File System