BIG_DATA_AND_IOT_MCQs

BIG DATA AND IOT 600 MCQs TOPIC ONE - Big Data Analysis and Extraction Techniques EASY QUESTIONS 1. Big data is the term used to describe the ______________ to process very large sets of data, which are often too com ...

BIG DATA AND IOT 600 MCQs TOPIC ONE - Big Data Analysis and Extraction Techniques EASY QUESTIONS 1. Big data is the term used to describe the ______________ to process very large sets of data, which are often too complex to process using regular database management tools. A. program B. Software C. machine D. application of specialized techniques Answer: D 2. Which one is not a common example of large data set A. Web logs B. Call records C. mouse D. Medical records Answer: C 3. Which ones are the Vs of Big Data?: A. Volume. B. Variety. C. Velocity. D. All of the above. Answer: D 4. What are the main components of Big Data? A. YARN. B. HDFS C. MapReduce D. All of the above. Answer: D 5. Genetic algorithms are inspired by inheritance, ___________ and natural selection. A. mutation B. human C. network D. computer Answer: A 6. Regression analysis is a ____________ that investigates the relationship between two or more variables. A. machine B. software C. powerful statistical method D. human Answer: C7. Sentiment Analysis is a type of ______________ technique that automates the process of understanding an opinion about a given subject from written or spoken language. A. machine. B. Natural Language Processing (NLP) C. writing. D. walking. Answer: B 8. NLP is as a sub specialty of computer science, artificial intelligence, and linguistics, which uses algorithms to analyse ___________. A. human (natural) language B. software C. money D. computers Answer: A 9. Which one is not an example of social media application that handles big data. A. facebook B. twitter C. youtube D. sms Answer: D 10. Data mining extracts patterns from large data sets by combining methods from statistics and ___________, within database management. A. tables B. food C. machine learning D. phones Answer: C INTERMEDIATE QUESTIONS 11. Which one below is a Big data analysis technique A. computer B. Association rule C. writing D. programming Answer: B 12. Which one is not a big data analytic techniques? A. Machine Learning. B. Regression analysis C. computer D. Data mining Answer: C 13. Which one is the biggest size of data below A. Megabytes B. Petabytes C. Terabytes D. KilobytesAnswer: B 14. ________________ is type of machine learning algorithm that adopts a structural mapping of binary decisions which lead to a decision about the class of an object. A. Classification tree analysis B. programming C. software D. Data Answer: A 15. Which technique is sometimes referred to as a decision tree? A. Data science B. Big data C. Classification tree analysis D. Natural language Answer: C 16. Which one below is a common applications of Genetic algorithms technique? A. eating B. writing code on computer C. traveling by bus D. scheduling of doctors for hospital emergency rooms Answer: D 17. Which one below gives computers the ability to learn without being explicitly programmed, thus it is able to make predictions based on known properties learned from sets of “training data. A. Firmware B. Machine Learning C. Human D. Middleware Answer: B 18. _______________ maps and measures the relationships and flows between people, groups, organizations, computers, URLs, and other connected information or knowledge entities.. A. Social network analysis B. computer C. email D. Cell phone Answer: A 19. ______________ extracts patterns from large data sets by combining methods from statistics and machine learning, within database management. A. Data B. Internet C. Data mining D. Computer Answer: C 20. Major supermarket chains to discover relations between products, using data from supermarket point-of-sale (POS) systems.A. counter. B. point-of-sale. C. machine D. human Answer: B 21. What does acronym NLP represents in big data techniques? A. Natural Language Products B. Nitrogen Liquid Products C. Natural Language Processing D. Nature List Pairs Answer: C 22. What does acronym ML represents in big data techniques? A. Material List B. Machine Learning C. Manufacturing Liquid D. Machine Language Answer: B 23. ______________ examines the influence of one or more independent variables on a dependent variable, like weight, speed or age. A. internet B. Big data C. neural network. D. Regression analysis Answer: D 24. Which of the following is an example of Machine learning application? A. cooking B. eating C. learning user preferences and make recommendations based on this information D. microwave and wireless transmissions. Answer: C 25. A ___________ helps researchers determine the sentiments of speakers or writers. A. human B. computer C. Sentiment analysis D. Internet Answer: C 26. The ______________ in the network represent the people and groups while the links identify the relationships or flows between the nodes. A. nodes B. human. C. light D. language Answer: A27. An example of the application of social network analysis include: A. running B. programming C. surfing D. determining the social structure of a customer base Answer: D 28. ____________ referred to as the process of finding anomalies, patterns and correlations within large data sets to predict outcomes. A surfing B. Data mining C. Big Data D. software Answer: B 29. If you have shopped online it is most likely that you were interacting with a ______ rather than an actual human being. A. cell phone. B. internet. C. human. D. chatbot Answer: D 30. ______ customer service agents are typically algorithms that use NLP to be able to understand your query and respond to your questions adequately, automatically, and in realtime. A. AL B. DL C. Data D. DM