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Business Intelligence and Analytics > Ch. 13 - Big Data and Analytics > Flashcards

Ch. 13 - Big Data and Analytics Flashcards

1
Q

The term “Big Data” is relative as it depends on the size of the using organization.

A

True

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2
Q

Many analytics tools are too complex for the average user, and this is one justification for Big Data.

A

True

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3
Q

Big Data uses commodity hardware, which is expensive, specialized hardware that is custom built for a client or application.

A

False

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4
Q

MapReduce can be easily understood by skilled programmers due to its procedural nature.

A

True

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5
Q

Hadoop was designed to handle petabytes and extabytes of data distributed over multiple nodes in parallel.

A

True

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6
Q

Hadoop and MapReduce require each other to work.

A

False

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7
Q

In most cases, Hadoop is used to replace data warehouses.

A

False

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8
Q

Despite their potential, many current NoSQL tools lack mature management and monitoring tools.

A

True

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9
Q

The data scientist is a profession for a field that is still largely being defined.

A

True

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10
Q

There is a current undersupply of data scientists for the Big Data market.

A

True

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11
Q

For low latency, interactive reports, a data warehouse is preferable to Hadoop.

A

True

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12
Q

If you have many flexible programming languages running in parallel, Hadoop is preferable to a data warehouse.

A

True

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13
Q

It is important for Big Data and self-service business intelligence go hand in hand to get maximum value from analytics.

A

True

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14
Q

Big Data simplifies data governance issues, especially for global firms.

A

False

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15
Q

Current total storage capacity lags behind the digital information being generated in the world.

A

True

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16
Q

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.

A

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

17
Q

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.

A

C) 10^15 bytes.

18
Q

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

A

C) RFID tags

19
Q

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

A

D) variability

20
Q

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

A) in-memory analytics

21
Q

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

A

C) grid computing

22
Q

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.

A

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

23
Q

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

A

B) unstructured and semistructured non-relational data

24
Q

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

A

C) a node where data is stored and processed

25
Q

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

A

B) secondary node

26
Q

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.

A

D) MapReduce runs without fault tolerance.

27
Q

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.

A

B) the variety and complexity of data.

28
Q

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

A

C) unrestricted, ungoverned sandbox explorations

29
Q

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.

A

B) Amazon and Google have working Hadoop cloud offerings.

30
Q

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

A) the largest computer and IT services firms.

31
Q

In the health sciences, the largest potential source of Big Data comes from
A) accounting systems.
B) human resources.
C) patient monitoring.
D) research administration.

A

C) patient monitoring.

32
Q

In the Discovery Health insurance case study, the analytics application used available data to help the company do all of the following EXCEPT
A) predict customer health.
B) detect fraud.
C) lower costs for members.
D) open its own pharmacy.

A

D) open its own pharmacy.

Business Intelligence and Analytics (6 decks)

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