Business Intelligence, 3e (Sharda/Delen/Turban)
Chapter 1 An Overview of Business Intelligence, Analytics, and Decision Support
1) Computerized support is only used for organizational decisions that are responses to external
pressures, not for taking advantage of opportunities.
2) The complexity of today’s business environment creates many new challenges for
organizations, such as global competition, but creates few new opportunities in return.
3) In addition to deploying business intelligence (BI) systems, companies may also perform other
actions to counter business pressures, such as improving customer service and entering business
alliances.
4) The overwhelming majority of competitive actions taken by businesses today feature
computerized information system support.
5) The access to data and ability to manipulate data (frequently including real-time data) are key
elements of business intelligence (BI) systems.
6) One of the four components of BI systems, business performance management, is a collection
of source data in the data warehouse.
7) Actionable intelligence is the primary goal of modern-day Business Intelligence (BI) systems
vs. historical reporting that characterized Management Information Systems (MIS).
8) Data warehouse and BI initiatives typically follow a process similar to that used in military
intelligence initiatives.
9) The two critical partnerships required for BI governance are (a) a partnership between
functional area users and/or product/service area employees, and (b) a partnership between
representatives of the marketing and vendor sides.
10) The term intelligence in a BI context is used to describe clandestine operations dedicated to
stealing corporate secrets, in the manner of the government’s CIA and other covert agencies.
11) Information systems that support such transactions as ATM withdrawals, bank deposits, and
cash register scans at the grocery store represent transaction processing, a critical branch of BI.
12) Many business users in the 1980s referred to their mainframes as “the black hole,” because
all the information went into it, but little ever came back and ad hoc real-time querying was
virtually impossible.
13) The success of BI is assured not because of which personnel would be the most likely to use
it, but as a result of pervasive adoption across the organization.
14) BI represents a bold new paradigm in which the company’s business strategy must be aligned
to its business intelligence analysis initiatives.
15) Traditional BI systems use a large volume of static data that has been extracted, cleansed,
and loaded into a data warehouse to produce reports and analyses.
16) Almost all BI applications are constructed with shells provided by an outsourcing provider
who may themselves create a custom solution for a vendor or work with another client.
17) The use of dashboards and data visualizations is seldom effective in finding efficiencies in
organizations, as demonstrated by the Seattle Children’s Hospital Case Study.
18) The use of statistics in baseball by the Oakland Athletics, as described in the Moneyball case
study, is an example of the effectiveness of prescriptive analytics.
19) Pushing programming out to distributed data is achieved solely by using the Hadoop
Distributed File System or HDFS.
20) Volume, velocity, and variety of data characterize the Big Data paradigm.
21) In the Magpie Sensing case study, the automated collection of temperature and humidity data
on shipped goods helped with various types of analytics. Which of the following is an example
of prescriptive analytics?
A) real time reports of the shipment’s temperature
B) warning of an open shipment seal
C) location of the shipment
D) optimal temperature setting
22) In the Magpie Sensing case study, the automated collection of temperature and humidity data
on shipped goods helped with various types of analytics. Which of the following is an example
of predictive analytics?
A) real time reports of the shipment’s temperature
B) warning of an open shipment seal
C) location of the shipment
D) optimal temperature setting
23) Which of the following is NOT an example that falls within the four major categories of
business environment factors for today’s organizations?
A) globalization
B) increased pool of customers
C) fewer government regulations
D) increased competition
24) Organizations counter the pressures they experience in their business environments in
multiple ways. Which of the following is NOT an effective way to counter these pressures?
A) reactive actions
B) anticipative actions
C) adaptive actions
D) retroactive actions
25) Business intelligence (BI) can be characterized as a transformation of
A) data to information to decisions to actions.
B) Big Data to data to information to decisions.
C) actions to decisions to feedback to information.
D) data to processing to information to actions.
26) In answering the question “Which customers are most likely to click on my online ads and
purchase my goods?” you are most likely to use which of the following analytic applications?
A) customer profitability
B) propensity to buy
C) customer attrition
D) channel optimization
27) In answering the question “Which customers are likely to be using fake credit cards?” you
are most likely to use which of the following analytic applications?
A) channel optimization
B) customer segmentation
C) fraud detection
D) customer profitability
28) When Sabre developed their Enterprise Data Warehouse, they chose to use near-real time
updating of their database. The main reason they did so was
A) to provide a 360 degree view of the organization.
B) to aggregate performance metrics in an understandable way.
C) to be able to assess internal operations.
D) to provide up-to-date executive insights.
29) Once a data warehouse is in place, the general process of intelligence creation begins with
A) end-user examinations of decision-making impacts.
B) identifying and prioritizing specific BI projects.
C) estimating the cost-benefit ratio of the ROI.
D) establishing the critical partnerships required for BI governance.
30) When middles look across an organization to ensure that project priorities reflect the needs
of the entire business, what is their main concern?
A) that their proprietary BI methods are protected from industrial espionage
B) that additional information available through an enterprise data warehouse should assist in
decision making
C) that a project does not just serve to sub-optimize one area over others
D) that return on investment (ROI) and total cost of ownership justify the cost—benefit ratio
31) Online transaction processing (OLTP) systems handle a company’s routine ongoing business.
In contrast, a data warehouse is typically
A) the end result of BI processes and operations.
B) a repository of actionable intelligence obtained from a data mart.
C) a distinct system that provides storage for data that will be made use of in analysis.
D) an integral subsystem of an online analytical processing (OLAP) system.
32) The very design that makes an OLTP system efficient for transaction processing makes it
inefficient for what?
A) end-user ad hoc reports, queries, and analysis
B) transaction processing systems that constantly update operational databases
C) the collection of reputable sources of intelligence
D) transactions such as ATM withdrawals, where we need to reduce a bank balance accordingly
33) What can the BI users in an organization help guide and direct?
A) how to implement and deploy a BI initiative that can be lengthy, expensive, and failure prone
B) how the DW is structured and the types of BI tools and other supporting software that are
needed
C) how to decompose the planning and execution into business, organization, functionality, and
infrastructure components
D) how the DW is structured and the costs and the appreciation for different classes of potential
users
34) If a company’s strategy is properly aligned with DW and BI initiatives, and if the company’s
IS organization can be made capable of playing its role in such a project, and if the requisite user
community is in place and has the proper motivation, then
A) it is no longer necessary to start BI within the company.
B) it is wise to start BI and establish a BI Competency Center (BICC) within the company.
C) the organization is ready for the introduction of new data-generating technologies, such as
radio-frequency identification (RFID).
D) business leaders are required to document their business processes and to sign off on the
legitimacy of the information they rely on.
35) What has caused the growth of the demand for instant, on-demand access to dispersed
information?
A) the increasing divide between users who focus on the strategic level and those who are more
oriented to the tactical level
B) the need to create a database infrastructure that is always online and contains all the
information from the OLTP systems
C) the more pressing need to close the gap between the operational data and strategic objectives
D) the fact that BI cannot simply be a technical exercise for the information systems department
36) Today, many vendors offer diversified tools, some of which are completely preprogrammed
(called shells). How are these shells utilized?
A) They are used for customization of BI solutions.
B) All a user needs to do is insert the numbers.
C) The shell provides a secure environment for the organization’s BI data.
D) They host an enterprise data warehouse that can assist in decision making.
37) How are descriptive analytics methods different from the other two types?
A) They answer “what-if?” queries, not “how many?” queries.
B) They answer “what-is?” queries, not “what will be?” queries.
C) They answer “what to do?” queries, not “what-if?” queries.
D) They answer “what will be?” queries, not “what to do?” queries.
38) Prescriptive BI capabilities are viewed as more powerful than predictive ones for all the
following reasons EXCEPT
A) prescriptive BI gives actual guidance as to actions.
B) understanding the likelihood of certain events often leaves unclear remedies.
C) only prescriptive BI capabilities have monetary value to top-level managers.
D) prescriptive models generally build on (with some overlap) predictive ones.
39) Which of the following statements about Big Data is true?
A) Data chunks are stored in different locations on one computer.
B) Hadoop is a type of processor used to process Big Data applications.
C) MapReduce is a storage filing system.
D) Pure Big Data systems do not involve fault tolerance.
40) Big Data often involves a form of distributed storage and processing using Hadoop and
MapReduce. One reason for this is
A) centralized storage creates too many vulnerabilities.
B) the “Big” in Big Data necessitates over 10,000 processing nodes.
C) the processing power needed for the centralized model would overload a single computer.
D) Big Data systems have to match the geographical spread of social media.
41) The desire by a customer to customize a product falls under the ________ category of
business environment factors.
42) An older and more diverse workforce falls under the ________ category of business
environment factors.
43) Organizations using BI systems are typically seeking to ________ the gap between the
organization’s current and desired performance.
44) ________ is an umbrella term that combines architectures, tools, databases, analytical tools,
applications, and methodologies.
45) A(n) ________ is a major component of a Business Intelligence (BI) system that holds
source data.
46) A(n) ________ is a major component of a Business Intelligence (BI) system that is usually
browser based and often presents a portal or dashboard.
47) ________ cycle times are now extremely compressed, faster, and more informed across
industries.
48) The fraud ________ analytic application helps determine fraudulent events and take action.
49) Sabre used executive ________ to present performance metrics in a concise way to its
executives.
50) Some organizations refer to the project prioritization process as a form of BI ________.
51) Applications based upon sensor and location data that contribute to the exponential growth of
collected raw data is called ________ identification.
52) Data warehouses are intended to work with informational data used for online ________
processing systems.
53) Many BI consultants and practitioners involved in successful BI initiatives advise that a
framework for ________ is a necessary precondition.
54) As the number of potential BI applications increases, the need to justify and prioritize them
arises. This is not an easy task due to the large number of ________ benefits.
55) ________ analytics help managers understand current events in the organization including
causes, trends, and patterns.
56) ________ analytics help managers understand probable future outcomes.
57) ________ analytics help managers make decisions to achieve the best performance in the
future.
58) The Google search engine is an example of Big Data in that it has to search and index
billions of ________ in fractions of a second for each search.
59) The filing system developed by Google to handle Big Data storage challenges is known as
the ________ Distributed File System.
60) The programing algorithm developed by Google to handle Big Data computational
challenges is known as ________.
61) The environment in which organizations operate today is becoming more and more complex.
Business environment factors can be divided into four major categories. What are these
categories?
62) What are the four major components of a Business Intelligence (BI) system?
63) What is a typical set of issues, as described in section 1.4, that the BI governance team needs
to address?
64) What is the intent of the analysis of data that is stored in a data warehouse?
65) Mention four possible functions that a BI Competency Center (BICC) would serve within an
organization, and give a brief description of each.
66) Business applications can be programmed to act on what real-time BI systems discover.
Describe two approaches to the implementation of real-time BI.
67) List and describe three levels or categories of analytics that are most often viewed as
sequential and independent, but also occasionally seen as overlapping.
68) How does Amazon.com use predictive analytics to respond to product searches by the
customer?
69) Describe and define Big Data. Why is a search engine a Big Data application?
70) What storage system and processing algorithm were developed by Google for Big Data?