Chapter 7 (BANK)

21) Using data to understand customers/clients and business operations to sustain and foster growth and profitability is A) easier with the advent of BI and Big Data. B) essentially the same now as it has always been. C) an increasingly challenging task for today's enterprises. D) now completely automated with no human intervention required.

C) an increasingly challenging task for today's enterprises.

27) Which Big Data approach promotes efficiency, lower cost, and better performance by processing jobs in a shared, centrally managed pool of IT resources? A) in-memory analytics B) in-database analytics C) grid computing D) appliances

C) grid computing

36) Under which of the following requirements would it be more appropriate to use Hadoop over a data warehouse? A) ANSI 2003 SQL compliance is required B) online archives alternative to tape C) unrestricted, ungoverned sandbox explorations D) analysis of provisional data

C) unrestricted, ungoverned sandbox explorations

33) In a network analysis, what connects nodes? A) edges B) metrics C) paths D) visualizations

A) edges

26) Allowing Big Data to be processed in memory and distributed across a dedicated set of nodes can solve complex problems in near-real time with highly accurate insights. What is this process called? A) in-memory analytics B) in-database analytics C) grid computing D) appliances

A) in-memory analytics

38) Companies with the largest revenues from Big Data tend to be A) the largest computer and IT services firms. B) small computer and IT services firms. C) pure open source Big Data firms. D) non-U.S. Big Data firms.

A) the largest computer and IT services firms.

22) A newly popular unit of data in the Big Data era is the petabyte (PB), which is A) 10^9 bytes. B) 10^12 bytes. C) 10^15 bytes. D) 10^18 bytes.

C) 10^15 bytes.

23) Which of the following sources is likely to produce Big Data the fastest? A) order entry clerks B) cashiers C) RFID tags D) online customers

C) RFID tags

30) In a Hadoop "stack," what is a slave node? A) a node where bits of programs are stored B) a node where metadata is stored and used to organize data processing C) a node where data is stored and processed D) a node responsible for holding all the source programs

C) a node where data is stored and processed

37) What is Big Data's relationship to the cloud? A) Hadoop cannot be deployed effectively in the cloud just yet. B) Amazon and Google have working Hadoop cloud offerings. C) IBM's homegrown Hadoop platform is the only option. D) Only MapReduce works in the cloud; Hadoop does not.

B) Amazon and Google have working Hadoop cloud offerings.

31) In a Hadoop "stack," what node periodically replicates and stores data from the Name Node should it fail? A) backup node B) secondary node C) substitute node D) slave node

B) secondary node

35) Traditional data warehouses have not been able to keep up with A) the evolution of the SQL language. B) the variety and complexity of data. C) expert systems that run on them. D) OLAP.

B) the variety and complexity of data.

29) What is the Hadoop Distributed File System (HDFS) designed to handle? A) unstructured and semistructured relational data B) unstructured and semistructured non-relational data C) structured and semistructured relational data D) structured and semistructured non-relational data

B) unstructured and semistructured non-relational data

28) How does Hadoop work? A) It integrates Big Data into a whole so large data elements can be processed as a whole on one computer. B) It integrates Big Data into a whole so large data elements can be processed as a whole on multiple computers. C) It breaks up Big Data into multiple parts so each part can be processed and analyzed at the same time on one computer. D) It breaks up Big Data into multiple parts so each part can be processed and analyzed at the same time on multiple computers.

D) It breaks up Big Data into multiple parts so each part can be processed and analyzed at the same time on multiple computers.

32) All of the following statements about MapReduce are true EXCEPT A) MapReduce is a general-purpose execution engine. B) MapReduce handles the complexities of network communication. C) MapReduce handles parallel programming. D) MapReduce runs without fault tolerance.

D) MapReduce runs without fault tolerance.

39) In the financial services industry, Big Data can be used to improve A) regulatory oversight. B) decision making. C) customer service. D) both A & B.

D) both A & B.

24) Data flows can be highly inconsistent, with periodic peaks, making data loads hard to manage. What is this feature of Big Data called? A) volatility B) periodicity C) inconsistency D) variability

D) variability