Deck 13: Big Data and Analytics

Question 1

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

Answer 1

False

Question 2

Hadoop and MapReduce require each other to work.

Answer 2

False

Question 3

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

Answer 3

True

Question 4

In the Dublin City Council case study, GPS data from the city's buses and CCTV were the only data sources for the Big Data GIS-based application.

Question 5

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

Question 6

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

Question 7

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

Question 8

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

Question 9

In the investment bank case study, the major benefit brought about by the supplanting of multiple databases by the new trade operational store was providing real-time access to trading data.

Question 10

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

Question 11

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

Question 12

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

Question 13

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

Question 14

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

Question 15

The Big Data and Analysis in Politics case study makes it clear that the unpredictability of elections makes politics an unsuitable arena for Big Data.

Question 16

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

Question 17

In the opening vignette, the CERN Data Aggregation System (DAS), built on MongoDB (a Big Data management infrastructure), used relational database technology.

Question 18

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

Question 19

In the Luxottica case study, outsourcing enhanced the ability of the company to gain insights into their data.

Question 20

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

Question 21

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.

Question 22

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

Question 23

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

Question 24

In the Luxottica case study, what technique did the company use to gain visibility into its customers?

A) visibility analytics
B) data integration
C) focus on growth
D) customer focus

Question 25

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.

Question 26

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.

Question 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

Question 28

In the Big Data and Analytics in Politics case study, what was the analytic system output or goal?

A) census data
B) assessment of sentiment
C) voter mobilization
D) group clustering

Question 29

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

Question 30

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.

Question 31

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.

Question 32

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.

Question 33

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.

Question 34

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

Question 35

A newly popular unit of data in the Big Data era is the petabyte (PB), which is

A) 10⁹ bytes.
B) 10¹² bytes.
C) 10¹⁵ bytes.
D) 10¹⁸ bytes.

Question 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

Question 37

In the Big Data and Analytics in Politics case study, which of the following was an input to the analytic system?

A) census data
B) assessment of sentiment
C) voter mobilization
D) group clustering

Question 38

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.

Question 39

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

Question 40

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

Question 41

The ________ Node in a Hadoop cluster provides client information on where in the cluster particular data is stored and if any nodes fail.

Question 42

In the world of Big Data, ________ aids organizations in processing and analyzing large volumes of multi-structured data. Examples include indexing and search, graph analysis, etc.

Question 43

The ________ of Big Data is its potential to contain more useful patterns and interesting anomalies than "small" data.

Question 44

________ speeds time to insights and enables better data governance by performing data integration and analytic functions inside the database.

Question 45

As the size and the complexity of analytical systems increase, the need for more ________ analytical systems is also increasing to obtain the best performance.

Question 46

In the energy industry, ________ grids are one of the most impactful applications of stream analytics.

Question 47

As volumes of Big Data arrive from multiple sources such as sensors, machines, social media, and clickstream interactions, the first step is to ________ all the data reliably and cost effectively.

Question 48

A job ________ is a node in a Hadoop cluster that initiates and coordinates MapReduce jobs, or the processing of the data.

Question 49

In open-source databases, the most important performance enhancement to date is the cost-based ________.

Question 50

________ refers to the conformity to facts: accuracy, quality, truthfulness, or trustworthiness of the data.

Question 51

HBase is a nonrelational ________ that allows for low-latency, quick lookups in Hadoop.

Question 52

In the U.S. telecommunications company case study, the use of analytics via dashboards has helped to improve the effectiveness of the company's ________ assessments and to make their systems more secure.

Question 53

________ bring together hardware and software in a physical unit that is not only fast but also scalable on an as-needed basis.

Question 54

Hadoop is primarily a(n) ________ file system and lacks capabilities we'd associate with a DBMS, such as indexing, random access to data, and support for SQL.

Question 55

Most Big Data is generated automatically by ________.

Question 56

Data ________ or pulling of data from multiple subject areas and numerous applications into one repository is the raison d'être for data warehouses.

Question 57

In-motion ________ is often overlooked today in the world of BI and Big Data.

Question 58

Big Data employs ________ processing techniques and nonrelational data storage capabilities in order to process unstructured and semistructured data.

Question 59

HBase, Cassandra, MongoDB, and Accumulo are examples of ________ databases.

Question 60

In the eBay use case study, load ________ helped the company meet its Big Data needs with the extremely fast data handling and application availability requirements.

Question 61

What is a data scientist and what does the job involve?

Question 62

Define MapReduce.

Question 63

Describe data stream mining and how it is used.

Question 64

What is NoSQL as used for Big Data? Describe its major downsides.

Question 65

What are the differences between stream analytics and perpetual analytics? When would you use one or the other?

Question 66

List and describe the three main "V"s that characterize Big Data.

Question 67

Why are some portions of tape backup workloads being redirected to Hadoop clusters today?

Question 68

In the opening vignette, what is the source of the Big Data collected at the European Organization for Nuclear Research or CERN?

Question 69

List and describe four of the most critical success factors for Big Data analytics.

Question 70

When considering Big Data projects and architecture, list and describe five challenges designers should be mindful of in order to make the journey to analytics competency less stressful.