methods
________ of data provides business value; pulling of data from multiple subject areas and numerous applications into one repository is the raison d'être for data warehouses.
Integration
AaaS in the cloud has economies of scale and scope by providing many ________ analytical applications with better scalability and higher cost savings.
virtual
The portion of the IoT technology infrastructure that focuses on controlling what and how information is captured is hardware. connectivity. software backend. applications.
applications.
The portion of the IoT technology infrastructure that focuses on how to manage incoming data and analyze it is hardware. connectivity. software backend. applications.
software backend.
Big Data simplifies data governance issues, especially for global firms. True False
False
Big Data simplifies data governance issues, especially for global firms. True False
False
Big Data uses commodity hardware, which is expensive, specialized hardware that is custom built for a client or application. True False
False
Big Data uses commodity hardware, which is expensive, specialized hardware that is custom built for a client or application. True False
False
Connectivity is not a part of the IoT infrastructure. True False
False
For cloud computing to be successful, users must have knowledge and experience in the control of the technology infrastructures. True False
False
IaaS helps provide faster information, but provides information only to managers in an organization. True False
False
SaaS combines aspects of cloud computing with Big Data analytics and empowers data scientists and analysts by allowing them to access centrally managed information data sets. True False
False
Users definitely own their biometric data. True False
False
Web-based e-mail such as Google's Gmail are not examples of cloud computing. True False
False
In this model, infrastructure resources like networks, storage, servers, and other computing resources are provided to client companies. DaaS SaaS IaaS PaaS
IaaS
How does Hadoop work? It breaks up Big Data into multiple parts so each part can be processed and analyzed at the same time on one computer. It integrates Big Data into a whole so large data elements can be processed as a whole on one computer. It integrates Big Data into a whole so large data elements can be processed as a whole on multiple computers. It breaks up Big Data into multiple parts so each part can be processed and analyzed at the same time on multiple computers.
It breaks up Big Data into multiple parts so each part can be processed and analyzed at the same time on multiple computers.
This model allows consumers to use applications and software that run on distant computers in the cloud infrastructure. SaaS IaaS DaaS PaaS
SaaS
This model allows consumers to use applications and software that run on distant computers in the cloud infrastructure. SaaS IaaS DaaS PaaS
SaaS
Why is separating the impact of analytics from that of other computerized systems a difficult task? The trend is toward integrating systems. Software tools are not sophisticated enough. It is not an organizational priority. Businesses do not typically track the sources of successful projects.
The trend is toward integrating systems.
Big Data is being driven by the exponential growth, availability, and use of information. True False
True
Current total storage capacity lags behind the digital information being generated in the world. True False
True
Current total storage capacity lags behind the digital information being generated in the world. True False
True
Despite their potential, many current NoSQL tools lack mature management and monitoring tools. True False
True
For low latency, interactive reports, a data warehouse is preferable to Hadoop. True False
True
From massive amounts of high-dimensional location data, algorithms that reduce the dimensionality of the data can be used to uncover trends, meaning, and relationships to eventually produce human-understandable representations. True False
True
Hadoop was designed to handle petabytes and exabytes of data distributed over multiple nodes in parallel. True False
True
Hadoop was designed to handle petabytes and exabytes of data distributed over multiple nodes in parallel. True False
True
If you have many flexible programming languages running in parallel, Hadoop is preferable to a data warehouse. True False
True
Internet of Things (IoT) is the phenomenon of connecting the physical world to the Internet. True False
True
It is important for Big Data and self-service business intelligence to go hand in hand to get maximum value from analytics. True False
True
It is important for Big Data and self-service business intelligence to go hand in hand to get maximum value from analytics. True False
True
MapReduce can be easily understood by skilled programmers due to its procedural nature. True False
True
RFID can be used in supply chains to manage product quality. True False
True
Satellite data can be used to evaluate the activity at retail locations as a source of alternative data. True False
True
Service-oriented DSS solutions generally offer individual or bundled services to the user as a service. True False
True
Social media mentions can be used to chart and predict flu outbreaks. True False
True
Social networking Web sites like Facebook, Twitter, and LinkedIn, are also examples of cloud computing. True False
True
The quality and objectivity of information disseminated by influential users of Twitter is higher than that disseminated by noninfluential users. True False
True
The term "Big Data" is relative as it depends on the size of the using organization. True False
True
The term cloud computing originates from a reference to the Internet as a "cloud" and represents an evolution of all of the previously shared/centralized computing trends. True False
True
________ refers to the conformity to facts: accuracy, quality, truthfulness, or trustworthiness of the data.
Veracity
With RFID tags, a(n) ________ tag has a battery on board to energize it.
active
Using data to understand customers/clients and business operations to sustain and foster growth and profitability is now completely automated with no human intervention required. an increasingly challenging task for today's enterprises. essentially the same now as it has always been. easier with the advent of BI and Big Data.
an increasingly challenging task for today's enterprises.
In the financial services industry, Big Data can be used to improve decision making. regulatory oversight. customer service. both A & B.
both A & B.
In the financial services industry, Big Data can be used to improve decision making. regulatory oversight. customer service. both A & B.
both A & B.
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.
capture
IaaS, AaaS and other ________-based offerings allow the rapid diffusion of advanced analysis tools among users, without significant investment in technology acquisition.
cloud
GPS Navigation is an example of which kind of location-based analytics? consumer-oriented geospatial static approach organization-oriented geospatial static approach consumer-oriented location-based dynamic approach organization-oriented location-based dynamic approach
consumer-oriented geospatial static approach
Analytics can change the way in which many ________ are made by managers and can consequently change their jobs.
decisions
In a network analysis, what connects nodes? edges visualizations paths metrics
edges
As the size and the complexity of analytical systems increase, the need for more ________ analytical systems is also increasing to obtain the best performance.
efficient
Which of these is NOT a part of the IoT technology infrastructure? electrical access software hardware connectivity
electrical access
Smartbin has developed trash containers that include sensors to detect weather. tip-over. types of trash. fill levels.
fill levels.
Smartbin has developed trash containers that include sensors to detect weather. tip-over. types of trash. fill levels.
fill levels.
Which Big Data approach promotes efficiency, lower cost, and better performance by processing jobs in a shared, centrally managed pool of IT resources? grid computing in-memory analytics in-database analytics appliances
grid computing
Which Big Data approach promotes efficiency, lower cost, and better performance by processing jobs in a shared, centrally managed pool of IT resources? grid computing in-memory analytics in-database analytics appliances
grid computing
The portion of the IoT technology infrastructure that focuses on the sensors themselves is hardware. connectivity. software backend. applications.
hardware.
In open-source databases, the most important performance enhancement to date is the cost-based ________.
optimizer
Big Data employs ________ processing techniques and nonrelational data storage capabilities in order to process unstructured and semistructured data.
parallel
For individual decision makers, ________ values constitute a major factor in the issue of ethical decision making.
personal
In general, ________ is the right to be left alone and the right to be free from unreasonable personal intrusion.
privacy
A(n) ________ is operated solely for a single organization having a mission critical workload and security concerns.
private cloud
In a(n) ________ the subscriber uses the resources offered by service providers over the Internet.
public cloud
Companies with the largest revenues from Big Data tend to be the largest computer and IT services firms. pure open source Big Data firms. small computer and IT services firms. non-U.S. Big Data firms.
the largest computer and IT services firms.
Companies with the largest revenues from Big Data tend to be the largest computer and IT services firms. pure open source Big Data firms. small computer and IT services firms. non-U.S. Big Data firms.
the largest computer and IT services firms.
Traditional data warehouses have not been able to keep up with the variety and complexity of data. the evolution of the SQL language. OLAP. expert systems that run on them.
the variety and complexity of data.
A major structural change that can occur when analytics are introduced into an organization is the creation of new organizational ________.
units
Data flows can be highly inconsistent, with periodic peaks, making data loads hard to manage. What is this feature of Big Data called? inconsistency volatility periodicity variability
variability
This model began with the notion that data quality could happen in a centralized place, cleansing and enriching data and offering it to different systems, applications, or users, irrespective of where they were in the organization, computers, or on the network. IaaS DaaS PaaS SaaS
DaaS
