Solution Manual for Business Intelligence: A Managerial Perspective on Analytics, 3/E 3rd Edition. Ramesh Sharda, Dursun Delen, Efraim Turban

Solution Manual for Business Intelligence: A
Managerial Perspective on Analytics, 3/E 3rd
Edition. Ramesh Sharda, Dursun Delen, Efraim
Turban download
https://testbankmall.com/product/solution-manual-for-business-
intelligence-a-managerial-perspective-on-analytics-3-e-3rd-
edition-ramesh-sharda-dursun-delen-efraim-turban/
Find test banks or solution manuals at testbankmall.com today!

We have selected some products that you may be interested in
Click the link to download now or visit testbankmall.com
for more options!.
Test bank for Business Intelligence: A Managerial
Perspective on Analytics, 3/E 3rd Edition. Ramesh Sharda,
Dursun Delen, Efraim Turban
https://testbankmall.com/product/test-bank-for-business-intelligence-
a-managerial-perspective-on-analytics-3-e-3rd-edition-ramesh-sharda-
dursun-delen-efraim-turban/
Solution Manual for Business Intelligence, Analytics, and
Data Science: A Managerial Perspective, 4th Edition,
Ramesh Sharda, Dursun Delen, Efraim Turban,
https://testbankmall.com/product/solution-manual-for-business-
intelligence-analytics-and-data-science-a-managerial-perspective-4th-
edition-ramesh-sharda-dursun-delen-efraim-turban/
Test Bank for Business Intelligence, Analytics, and Data
Science: A Managerial Perspective, 4th Edition, Ramesh
Sharda, Dursun Delen Efraim Turban
https://testbankmall.com/product/test-bank-for-business-intelligence-
analytics-and-data-science-a-managerial-perspective-4th-edition-
ramesh-sharda-dursun-delen-efraim-turban/
Test Bank for Essentials of Anatomy and Physiology, 8th
Edition, Valerie C. Scanlon, Tina Sanders,
https://testbankmall.com/product/test-bank-for-essentials-of-anatomy-
and-physiology-8th-edition-valerie-c-scanlon-tina-sanders/

Test Bank for Management 9th by Kinicki
https://testbankmall.com/product/test-bank-for-management-9th-by-
kinicki/
Test Bank for Essentials of Pediatric Nursing, 1st
Edition: Theresa Kyle
https://testbankmall.com/product/test-bank-for-essentials-of-
pediatric-nursing-1st-edition-theresa-kyle/
Solution manual for Financial and Managerial Accounting
Williams Haka Bettner Carcello 16th edition
https://testbankmall.com/product/solution-manual-for-financial-and-
managerial-accounting-williams-haka-bettner-carcello-16th-edition/
CURRENT Medical Diagnosis and Treatment 2019 58th Edition
Test Bank
https://testbankmall.com/product/current-medical-diagnosis-and-
treatment-2019-58th-edition-test-bank/
Test Bank for America A Narrative History Brief, 11th
Edition, Combined Volume, David E Shi
https://testbankmall.com/product/test-bank-for-america-a-narrative-
history-brief-11th-edition-combined-volume-david-e-shi/

Test Bank for Assembly Language for x86 Processors, 7/E
7th Edition Kip R. Irvine
https://testbankmall.com/product/test-bank-for-assembly-language-
for-x86-processors-7-e-7th-edition-kip-r-irvine/

2
ScholarStock
CHAPTER OVERVIEW
The concept of data warehousing has been around since the late 1980s. This chapter
provides the foundation for an important type of database, called a data warehouse,
which is primarily used for decision support and provides improved analytical
capabilities. We discuss data warehousing in the following sections:
CHAPTER OUTLINE
2.1 OPENING VIGNETTE: ISLE OF CAPRI CASINOS IS WINNING WITH
ENTERPRISE DATA WAREHOUSE
 Questions for the Opening Vignette
A. WHAT WE CAN LEARN FROM THIS VIGNETTE
2.2 DATA WAREHOUSING DEFINITIONS AND CONCEPTS
A. WHAT IS A DATA WAREHOUSE?
B. A HISTORICAL PERSPECTIVE TO DATA WAREHOUSING
C. CHARACTERISTICS OF DATA WAREHOUSING
D. DATA MARTS
E. OPERATIONAL DATA STORES
F. ENTERPRISE DATA WAREHOUSES (EDW)
⧫ Application Case 2.1: A Better Data Plan: Well-Established
TELCOs Leverage Data Warehousing and Analytics to
Stay on Top in a Competitive Industry
G. METADATA
 Section 2.2 Review Questions
2.3 DATA WAREHOUSING PROCESS OVERVIEW
⧫ Application Case 2.2: Data Warehousing Helps MultiCare
Save More Lives
2.4 DATA WAREHOUSING ARCHITECTURES
A. ALTERNATIVE DATA WAREHOUSING ARCHITECTURES
B. WHICH ARCHITECTURE IS THE BEST?
2.5 DATA INTEGRATION AND THE EXTRACTION, TRANSFORMATION,
AND LOAD (ETL) PROCESSES
A. DATA INTEGRATION
⧫ Application Case 2.3: BP Lubricants Achieves BIGS
Success
B. EXTRACTION, TRANSFORMATION, AND LOAD

3
ScholarStock
2.6 DATA WAREHOUSE DEVELOPMENT
⧫ Application Case 2.4: Things Go Better with Coke’s Data
Warehouse
A. DATA WAREHOUSE DEVELOPMENT APPROACHES
1. The Inmon Model: The EDW Approach
2. The Kimball Model: The Data Mart Approach
3. Which Model Is Best?
⧫ Application Case 2.5: Starwood Hotels & Resorts Manages
Hotel Profitability with Data Warehousing
B. ADDITIONAL DATA WAREHOUSE DEVELOPMENT
CONSIDERATIONS
⧫ Technology Insights 2.1: Hosted Data Warehouses
C. REPRESENTATION OF DATA IN DATA WAREHOUSE
D. ANALYSIS OF DATA IN DATA WAREHOUSE
E. OLAP VERSUS OLTP
F. OLAP OPERATIONS
1. Variations of OLAP
⧫ Technology Insights 2.2: Hands-On Data Warehousing
with MicroStrategy
2.7 DATA WAREHOUSING IMPLEMENTATION ISSUES
⧫ Application Case 2.6: EDW Helps Connect State Agencies
in Michigan
A. MASSIVE DATA WAREHOUSES AND SCALABILITY
2.8 REAL-TIME DATA WAREHOUSING
⧫ Application Case 2.7: Egg Plc Fries the Competition in
Near Real Time
⧫ Technology Insights 2.3: The Real-Time Realities of
Active Data Warehousing
2.9 DATA WAREHOUSE ADMINISTRATION, SECURITY ISSUES, AND
FUTURE TRENDS
⧫ Technology Insights 2.4: Ambeo Delivers Proven Data-
Access Auditing Solution
A. THE FUTURE OF DATA WAREHOUSING
2.10 RESOURCES, LINKS, AND THE TERADATA UNIVERSITY NETWORK
CONNECTION
A. RESOURCES AND LINKS
B. CASES
C. VENDORS, PRODUCTS, AND DEMOS

4
ScholarStock
D. PERIODICALS
E. ADDITIONAL REFERENCES
F. THE TERADATA UNIVERSITY NETWORK (TUN) CONNECTION
Chapter Highlights
Key Terms
Questions for Discussion
Exercises
Teradata University and Other Hands-On Exercises
Team Assignments and Role-Playing Projects
Internet Exercises
⧫ End of Chapter Application Case: Continental Airlines
Flies High with Its Real-Time Data Warehouse
 Questions for the Case
References
TEACHING TIPS/ADDITIONAL INFORMATION        
Expect to spend some time on this chapter, as understanding its content is crucial and
many of the concepts are not intuitive to students whose major computer exposure has
been at the personal level. You should prepare yourself with some technical examples of
how things work, such as screen shots from some of the tools mentioned in the chapter,
as most of the technical discussion here is at a more conceptual level. The business
discussion is tangible, but the technical part is less so. It will be up to you to connect it to
the students.
Section 2.2 defines several fundamental concepts. Students must understand that these
are not definitions for the sake of definitions (every textbook has some of those, this one
is no exception) but are important to anyone working in the field. The characteristics of a
data warehouse in its extended definition, for example, are given not because some
researcher thought they’d be theoretically nice, but, more specifically, because they’ve
turned out to be important in practice. So, it’s important to really know what each of them
is about. (The concept of an operational data store should already be familiar to students,
though perhaps not by that name. They should know what metadata are from their use
with general databases, too.)
ANSWERS TO END OF SECTION REVIEW QUESTIONS     
Section 2.1 Review Questions
1. Why is it important for Isle to have an EDW?
In the gaming industry, companies distinguish themselves based on their customer
relationships. An enterprise data warehouse (EDW) gathers and provides the data
needed to tell Isle of Capri what customers respond to, so the casinos can adapt

5
ScholarStock
their offerings. The information provided by the EDW lets Isle deepen its
understanding of customers, so it can efficiently give them more of the kinds of
entertainment they are looking for.
2. What were the business challenges or opportunities that Isle was facing?
Isle of Capri Casinos is one of the largest publicly traded gaming companies in
the United States, but the gaming business is competitive. Other casinos offer
essentially the same games, so Isle must find ways to make its entertainment and
hospitality atmosphere one that exceeds customer expectations. Before Isle
implemented the EDW, casino managers had to wait to review monthly data until
the second week of the following month. The time lag made it difficult for casinos
to identify what actions were appealing to customers in time to respond. Adding
to these business challenges, Hurricane Katrina set back initial efforts to set up a
data warehouse at the southeastern company.
3. What was the process Isle followed to realize EDW? Comment on the potential
challenges Isle might have had going through the process of EDW development.
Isle of Capri brought in two expert suppliers. Teradata provided the core solution;
IBM Cognos provided expertise in business intelligence. Isle hired a management
team that understood how EDW could support decision making at Isle. That team
would be able to help Isle’s managers with the challenge of understanding how
they can frame queries and follow-up questions to figure out ways to improve the
business. Most likely, the potential of using detailed, up-to-the-minute data would
be unfamiliar to many of these managers.
4. What were the benefits of implementing an EDW at Isle? Can you think of other
potential benefits that were not listed in the case?
The implementation of EDW brought several benefits related to the timeliness
and detail of the data that became available. Instead of five week-old monthly
reports, managers can now study a variety of daily, weekly, and monthly reports.
The reports segment data by particular properties and customer groups, so
managers can zero in on particular problems and successes, easily making
comparisons among properties. Managers can submit queries about data sets and
receive information within minutes. In this way, managers can find out how
particular promotions are affecting customer behavior at particular casinos. The
EDW also connects data about casino activity with data about customers’ use of
hotels and efforts by Isle’s hosts. This, too, helps the company target promotions
and offer customers incentives they value. Even decisions as detailed as where to
locate slot machines can be adjusted to boost profits based on data from the EDW.
5. Why do you think large enterprises like Isle in the gaming industry can succeed
without having a capable data warehouse/business intelligence infrastructure?

6
ScholarStock
In the past, businesses in the gaming industry could succeed without a capable
data warehouse/business intelligence infrastructure because their managers knew
as much about customers as their competitors’ management knew. They were all
testing ideas for promotion or entertainment and responding to customer behavior
at about the same pace. However, when one company such as Isle begins to
respond to daily, property-by-property data, choosing the marketing and
entertainment options that deliver exactly what most profitably lures customers,
competitors without that capability will soon begin to suffer.
1. What is a data warehouse?
A data warehouse is defined in this section as “a pool of data produced to support
decision making.” This focuses on the essentials, leaving out characteristics that
may vary from one DW to another but are not essential to the basic concept.
The same paragraph gives another definition: “a subject-oriented, integrated,
time-variant, nonvolatile collection of data in support of management’s decision-
making process.” This definition adds more specifics, but in every case
appropriately: it is hard, if not impossible, to conceive of a data warehouse that
would not be subject-oriented, integrated, etc.
2. How does a data warehouse differ from a database?
Technically a data warehouse is a database, albeit with certain characteristics to
facilitate its role in decision support. Specifically, however, it is (see previous
question) an “integrated, time-variant, nonvolatile, subject-oriented repository of
detail and summary data used for decision support and business analytics within
an organization.” These characteristics, which are discussed further in the section
just after the definition, are not necessarily true of databases in general—though
each could apply individually to a given one.
As a practical matter most databases are highly normalized, in part to avoid
update anomalies. Data warehouses are highly denormalized for performance
reasons. This is acceptable because their content is never updated, just added to.
Historical data are static.
3. What is an ODS?
Operational Data Store is the database from which a business operates on an on-
going basis.
4. Differentiate among a data mart, an ODS, and an EDW.

7
ScholarStock
An ODS (Operational Data Store) is the database from which a business operates
on an ongoing basis.
Both an EDW and a data mart are data warehouses. An EDW (Enterprise Data
Warehouse) is an all-encompassing DW that covers all subject areas of interest to
the entire organization. A data mart is a smaller DW designed around one
problem, organizational function, topic, or other suitable focus area.
5. Explain the importance of metadata.
Metadata, “data about data,” are the means through which applications and users
access the content of a data warehouse, through which its security is managed,
and through which organizational management manages, in the true sense of the
word, its information assets. Most database management systems would be unable
to function without at least some metadata. Indeed, the use of metadata, which
enable data access through names and logical relationships rather than physical
locations, is fundamental to the very concept of a DBMS.
Metadata are essential to any database, not just a data warehouse. (See answer to
Review Question 2 of this section above.)
1. Describe the data warehousing process.
The data warehousing process consists of the following steps:
1. Data are imported from various internal and external sources
2. Data are cleansed and organized consistently with the organization’s needs
3. a. Data are loaded into the enterprise data warehouse, or
b. Data are loaded into data marts.
4. a. If desired, data marts are created as subsets of the EDW, or
b. The data marts are consolidated into the EDW
5. Analyses are performed as needed
2. Describe the major components of a data warehouse.
• Data sources. Data are sourced from operational systems and possibly
from external data sources.
• Data extraction and transformation. Data are extracted and properly
transformed using custom-written or commercial software called ETL.
• Data loading. Data are loaded into a staging area, where they are
transformed and cleansed. The data are then ready to load into the data
warehouse.
• Comprehensive database. This is the EDW that supports decision analysis
by providing relevant summarized and detailed information.

8
ScholarStock
• Metadata. Metadata are maintained for access by IT personnel and users.
Metadata include rules for organizing data summaries that are easy to
index and search.
• Middleware tools. Middleware tools enable access to the data warehouse
from a variety of front-end applications.
3. Identify and discuss the role of middleware tools.
Middleware tools enable access to the data warehouse. Power users such as
analysts may write their own SQL queries. Others may access data through a
managed query environment. There are many front-end applications that business
users can use to interact with data stored in the data repositories, including data
mining, OLAP, reporting tools, and data visualization tools. All these have their
own data access requirements. Those may not match with how a given data
warehouse must be accessed. Middleware translates between the two.
1. What are the key similarities and differences between a two-tiered architecture
and a three-tiered architecture?
Both provide the same user visibility through a client system that accesses a
DSS/BI application remotely. The difference is behind the scenes and is invisible
to the user: in a two-tiered architecture, the application and data warehouse reside
on the same machine; in a three-tiered architecture, they are on separate machines.
2. How has the Web influenced data warehouse design?
Primarily by making Web-based data warehousing possible.
3. List the alternative data warehousing architectures discussed in this section.
• Independent data marts architecture
• Data mart bus architecture with linked dimensional data marts
• Hub-and-spoke architecture (corporate information factory)
• Centralized data warehouse architecture
• Federated architecture
4. What issues should be considered when deciding which architecture to use in
developing a data warehouse? List the 10 most important factors.
1. Information interdependence between organizational units
2. Upper management’s information needs
3. Urgency of need for a data warehouse
4. Nature of end-user tasks

9
ScholarStock
5. Constraints on resources
6. Strategic view of the data warehouse prior to implementation
7. Compatibility with existing systems
8. Perceived ability of the in-house IT staff
9. Technical issues
10. Social/political factors
(This list from the text, while clearly intended by the authors as the answer to this
review question, does not explicitly say that these are the ten most important
factors. Students may choose others.)
5. Which data warehousing architecture is the best? Why?
See Table 2.1 Average Assessment Scores for the Success of the Architectures.
What is interesting is the similarity of the averages for the bus, hub-and-spoke,
and centralized architectures. The differences are sufficiently small that no claims
can be made for a particular architecture’s superiority over the others, at least
based on a simple comparison of these success measures.
1. Describe data integration.
Data integration is an umbrella term that covers three processes that combine to
move data from multiple sources into a data warehouse: accessing the data,
combining different views of the data, and capturing changes to the data.
2. Describe the three steps of the ETL process.
Extraction: selecting data from one or more sources and reading the selected data.
Transformation: converting data from their original form to whatever form the
DW needs. This step often also includes cleansing of the data to remove as many
errors as possible.
Load: putting the converted (transformed) data into the DW.
3. Why is the ETL process so important for data warehousing efforts?
Since ETL is the process through which data are loaded into a data warehouse, a
DW could not exist without it. The ETL process also contributes to the quality of
the data in a DW.

10
ScholarStock
1. List the benefits of data warehouses.
Direct benefits include:
• Allowing end users to perform extensive analysis in numerous ways.
• A consolidated view of corporate data (i.e., a single version of the truth).
• Better and more timely information. A data warehouse permits
information processing to be offloaded from costly operational systems
onto low-cost servers; therefore, end-user information requests can be
processed more quickly.
• Enhanced system performance. A data warehouse frees production
processing because some operational system reporting requirements are
moved to DSS.
• Simplification of data access.
Indirect benefits arise when end users take advantage of these direct benefits.
2. List several criteria for selecting a data warehouse vendor, and describe why they
are important.
Six important criteria are: financial strength, ERP linkages, qualified consultants,
market share, industry experience, and established partnerships. These are
important to indicate that a vendor is likely to be in business for the long term, to
have the support capabilities its customers need, and to provide products that
interoperate with other products the potential user has or may obtain.
One could add others, such as product functionality (Does it do what we need?),
vendor strategic vision (Does their direction make sense for our future plans
and/or is it consistent with industry trends?) and quality of customer references
(What do their existing customers think of them?).
3. What is OLAP and how does it differ from OLTP?
Data stored in a data warehouse can be analyzed using techniques referred to as
OLAP. OLAP is one of the most commonly used data analysis techniques in data
warehouses. OLAP is an approach to quickly answer ad hoc questions that require
data analysis.
OLTP is concerned with the capture and storage of data. OLAP is concerned with
the analysis of that data.
4. What is a cube? What do drill down, roll up, and slice and dice mean?
The main operational structure in OLAP is based on a concept called cube. A
cube in OLAP is a multidimensional data structure (actual or virtual) that allows
fast analysis of data.

11
ScholarStock
Using OLAP, an analyst can navigate through the database and screen for a
particular subset of the data (and its progression over time) by changing the data’s
orientations and defining analytical calculations. These types of user-initiated
navigation of data through the specification of slices (via rotations) and drill
down/up (via aggregation and disaggregation) are sometimes called “slice and
dice.” Commonly used OLAP operations include slice and dice, drill down, roll
up, and pivot.
• Slice: A slice is a subset of a multidimensional array (usually a two-
dimensional representation) corresponding to a single value set for one (or
more) of the dimensions not in the subset.
• Dice: The dice operation is a slice on more than two dimensions of a data
cube.
• Drill Down/Up: Drilling down or up is a specific OLAP technique
whereby the user navigates among levels of data ranging from the most
summarized (up) to the most detailed (down).
5. What are ROLAP, MOLAP, and HOLAP? How do they differ from OLAP?
ROLAP stands for Relational Online Analytical Processing. ROLAP is an
alternative to the MOLAP (Multidimensional OLAP) technology. While both
ROLAP and MOLAP analytic tools are designed to allow analysis of data through
the use of a multidimensional data model, ROLAP differs in that it does not
require the pre-computation and storage of information. Instead, ROLAP tools
access the data in a relational database and generate SQL queries to calculate
information at the appropriate level when an end user requests it. MOLAP is an
alternative to the ROLAP technology. MOLAP differs from ROLAP significantly
in that it requires the pre-computation and storage of information in the cube—
the operation known as preprocessing. MOLAP stores this data in an optimized
multidimensional array storage, rather than in a relational database.
HOLAP (Hybrid Online Analytical Processing) is a combination of ROLAP and
MOLAP. HOLAP allows storing part of the data in a MOLAP store and another
part of the data in a ROLAP store. The degree of control that the cube designer
has over this partitioning varies from product to product.
All of these are variations of OLAP.
1. What are the major DW implementation tasks that can be performed in parallel?

12
ScholarStock
Reeves (2009) and Solomon (2005) provided some guidelines regarding the
critical questions that must be asked, some risks that should be weighted, and
some processes that can be followed to help ensure a successful data warehouse
implementation. They compiled a list of 11 major tasks that could be performed in
parallel:
Establishment of service-level agreements and data-refresh requirements
Identification of data sources and their governance policies
Data quality planning
Data model design
ETL tool selection
Relational database software and platform selection
Data transport
Data conversion
Reconciliation process
Purge and archive planning
End-user support
2. List and discuss the most pronounced DW implementation guidelines.
• Senior management must support development of the data warehouse. The
DW needs a project champion at a high position in the organization chart.
Benefits of a DW project may be difficult to measure, so management
support makes it more likely the project will receive funding.
• Web-based data warehouses may need special security requirements.
These ensure that only authorized users have access to the data.
• Users should participate in the development process. Their participation is
essential for data modeling and access modeling. User participation
ensures that the DW includes the needed data and that decision makers can
retrieve the data they need.
• DW implementation requires certain skills from members of the
development team: in-depth knowledge of database technology and the
development tools used.
3. When developing a successful data warehouse, what are the most important risks
and issues to consider and potentially avoid?
• Starting with the wrong sponsorship chain

13
ScholarStock
• Setting expectations that you cannot meet
• Engaging in politically naive behavior
• Loading the data warehouse with information just because it is available
• Believing that data warehousing database design is the same as
transactional database design
• Choosing a data warehouse manager who is technology oriented rather
than user oriented
• Focusing on traditional internal record-oriented data and ignoring the
value of external data and of text, images, and, perhaps, sound and video
• Delivering data with overlapping and confusing definitions
• Believing promises of performance, capacity, and scalability
• Believing that your problems are over when the data warehouse is up and
running
• Focusing on ad hoc data mining and periodic reporting instead of alerts
4. What is scalability? How does it apply to DW?
Scalability refers to the degree to which a system can adjust to changes in demand
without major additional changes or investments. DW scalability issues are the
amount of data in the warehouse, how quickly the warehouse is expected to grow,
the number of concurrent users, and the complexity of user queries. A data
warehouse must scale both horizontally and vertically. The warehouse will grow
as a function of data growth and the need to expand the warehouse to support new
business functionality. Data growth may be a result of the addition of current
cycle data (e.g., this month’s results) and/or historical data.
1. What is an RDW?
A real-time data warehouse, in which decision-making data are updated on an
ongoing basis as business transactions occur; same as an active data warehouse
(ADW).
2. List the benefits of an RDW.

14
ScholarStock
The RDW extends the benefits of data warehousing, in general, down into
tactical, and perhaps operational, decision making. It empowers people who
interact directly with customers and suppliers by providing them with information
to make decisions. It can then be extended to customers and suppliers themselves,
thus affecting almost all aspects of customer service, SCM, logistics, and beyond.
It can also facilitate e-business activities, as when sales outlets such as
overstock.com (cited in the text) use historical data to price new close-outs.
3. What are the major differences between a traditional data warehouse and an
RDW?
1. A traditional data warehouse (TDW) is used for strategic decisions (and
sometimes tactical); an RDW for strategic and tactical (sometimes
operational) ones.
2. The results of using a TDW can be hard to measure; results of using an
RDW are measured by operational data.
3. Acceptable TDW refresh rates range from daily to monthly; RDW data
must be up to the minute.
4. TDW summaries are often appropriate; RDWs must supply detailed data.
5. Small user community at upper organizational levels means a TDW
supports few concurrent users; an RDW must support many, perhaps over
a thousand.
6. TDWs typically use restrictive reporting to confirm or check patterns,
often predefined summary tables; RDWs need flexible, ad hoc reporting.
7. TDW user community generally consists of power users, knowledge
workers, managers, other internal users; RDWs are used by operational
staff, call centers, perhaps external users.
4. List some of the drivers for RDW.
• A business often cannot afford to wait a whole day for its operational data
to load into the data warehouse for analysis.
• Traditional data warehouses have captured snapshots of an organization’s
fixed states instead of incremental real-time data showing every state
change and almost analogous patterns over time.
• With a traditional hub-and-spoke architecture, retaining the metadata in
sync is difficult. It is also costly to develop, maintain, and secure many
systems as opposed to one huge data warehouse so that data are
centralized for BI/BA tools.
• In cases of huge nightly batch loads, the necessary ETL setup and
processing power for large nightly data warehouse loading might be very
high, and the processes might take too long. An EAI with real-time data
collection can reduce or eliminate the nightly batch processes.

15
ScholarStock
1. What steps can an organization take to ensure the security and confidentiality of
customer data in its data warehouse?
Effective security in a data warehouse should focus on four main areas:
Step 1. Establishing effective corporate and security policies and procedures. An
effective security policy should start at the top and be communicated to
everyone in the organization.
Step 2. Implementing logical security procedures and techniques to restrict access.
This includes user authentication, access controls, and encryption.
Step 3. Limiting physical access to the data center environment.
Step 4. Establishing an effective internal control review process for security and
privacy.
2. What skills should a DWA possess? Why?
• Familiarity with high-performance hardware, software, and networking
technologies, since the data warehouse is based on those
• Solid business insight, to understand the purpose of the DW and its
business justification
• Familiarity with business decision-making processes to understand how
the DW will be used
• Excellent communication skills, to communicate with the rest of the
organization
3. What recent technologies may shape the future of data warehousing? Why?
Following are some of the recently popularized concepts and technologies that
will play a significant role in defining the future of data warehousing.
Sourcing: Acquisition of data from diverse and dispersed sources
• Web, social media, and Big Data
• Open source software
• SaaS (software as a service) “The Extended ASP Model”
• Cloud computing
Infrastructure: Architectural—hardware and software—enhancements
• Columnar (a new way to score and access data in the database)

16
ScholarStock
• Real-time data warehousing
• Data warehouse appliances (all-in-one solutions to DW)
• Data management technologies and practices
• In-database processing technology (putting the algorithms where the data is)
• In-memory storage technology (moving the data in the memory for faster
processing)
• New database management systems
• Advanced analytics
As the world of business becomes more global and complex, the need for business
intelligence and data warehousing tools also becomes more prominent. The fast
improving information technology tools and techniques seem to be moving in the
right direction to address the needs of the future business intelligence systems.
(This section has no review questions.)
ANSWERS TO APPLICATION CASE QUESTIONS FOR DISCUSSION 
Application Case 2.1: A Better Data Plan: Well-Established TELCOs Leverage
Data Warehousing and Analytics to Stay on Top in a Competitive Industry
1. What are the main challenges for TELCOs?
To stay competitive, TELCOs must continuously refine everything from customer
service to plan pricing. The major challenges faced by both entrenched and new
companies in this industry include: retaining customers, decreasing costs, fine-
tuning pricing models, improving customer satisfaction, acquiring new customers,
and understanding the role of social media in customer loyalty.
2. How can data warehousing and data analytics help TELCOs in overcoming their
challenges?
Highly targeted data analytics play an ever more critical role in helping carriers
secure or improve their standing in an increasingly competitive marketplace.
Argentina’s Telefónica de Argentina used analytics for its “traceability project,”
which tracked the factors involved in customer churn, a big problem among

Random documents with unrelated
content Scribd suggests to you:

Transcriber’s Notes
Silently corrected a few typos.
Retained publication information from the printed edition: this
eBook is public-domain in the country of publication.
Added explanatory text {in brackets} for unfamiliar brand
names.
In the text versions only, text in italics is delimited by
_underscores_.

*** END OF THE PROJECT GUTENBERG EBOOK RECIPES FROM
AMERICAN NATIONAL ***
Updated editions will replace the previous one—the old editions will
be renamed.
Creating the works from print editions not protected by U.S.
copyright law means that no one owns a United States copyright in
these works, so the Foundation (and you!) can copy and distribute it
in the United States without permission and without paying
copyright royalties. Special rules, set forth in the General Terms of
Use part of this license, apply to copying and distributing Project
Gutenberg™ electronic works to protect the PROJECT GUTENBERG™
concept and trademark. Project Gutenberg is a registered trademark,
and may not be used if you charge for an eBook, except by following
the terms of the trademark license, including paying royalties for use
of the Project Gutenberg trademark. If you do not charge anything
for copies of this eBook, complying with the trademark license is
very easy. You may use this eBook for nearly any purpose such as
creation of derivative works, reports, performances and research.
Project Gutenberg eBooks may be modified and printed and given
away—you may do practically ANYTHING in the United States with
eBooks not protected by U.S. copyright law. Redistribution is subject
to the trademark license, especially commercial redistribution.
START: FULL LICENSE

THE FULL PROJECT GUTENBERG LICENSE

PLEASE READ THIS BEFORE YOU DISTRIBUTE OR USE THIS WORK
To protect the Project Gutenberg™ mission of promoting the free
distribution of electronic works, by using or distributing this work (or
any other work associated in any way with the phrase “Project
Gutenberg”), you agree to comply with all the terms of the Full
Project Gutenberg™ License available with this file or online at
www.gutenberg.org/license.
Section 1. General Terms of Use and
Redistributing Project Gutenberg™
electronic works
1.A. By reading or using any part of this Project Gutenberg™
electronic work, you indicate that you have read, understand, agree
to and accept all the terms of this license and intellectual property
(trademark/copyright) agreement. If you do not agree to abide by all
the terms of this agreement, you must cease using and return or
destroy all copies of Project Gutenberg™ electronic works in your
possession. If you paid a fee for obtaining a copy of or access to a
Project Gutenberg™ electronic work and you do not agree to be
bound by the terms of this agreement, you may obtain a refund
from the person or entity to whom you paid the fee as set forth in
paragraph 1.E.8.
1.B. “Project Gutenberg” is a registered trademark. It may only be
used on or associated in any way with an electronic work by people
who agree to be bound by the terms of this agreement. There are a
few things that you can do with most Project Gutenberg™ electronic
works even without complying with the full terms of this agreement.
See paragraph 1.C below. There are a lot of things you can do with
Project Gutenberg™ electronic works if you follow the terms of this
agreement and help preserve free future access to Project
Gutenberg™ electronic works. See paragraph 1.E below.

1.C. The Project Gutenberg Literary Archive Foundation (“the
Foundation” or PGLAF), owns a compilation copyright in the
collection of Project Gutenberg™ electronic works. Nearly all the
individual works in the collection are in the public domain in the
United States. If an individual work is unprotected by copyright law
in the United States and you are located in the United States, we do
not claim a right to prevent you from copying, distributing,
performing, displaying or creating derivative works based on the
work as long as all references to Project Gutenberg are removed. Of
course, we hope that you will support the Project Gutenberg™
mission of promoting free access to electronic works by freely
sharing Project Gutenberg™ works in compliance with the terms of
this agreement for keeping the Project Gutenberg™ name associated
with the work. You can easily comply with the terms of this
agreement by keeping this work in the same format with its attached
full Project Gutenberg™ License when you share it without charge
with others.
1.D. The copyright laws of the place where you are located also
govern what you can do with this work. Copyright laws in most
countries are in a constant state of change. If you are outside the
United States, check the laws of your country in addition to the
terms of this agreement before downloading, copying, displaying,
performing, distributing or creating derivative works based on this
work or any other Project Gutenberg™ work. The Foundation makes
no representations concerning the copyright status of any work in
any country other than the United States.
1.E. Unless you have removed all references to Project Gutenberg:
1.E.1. The following sentence, with active links to, or other
immediate access to, the full Project Gutenberg™ License must
appear prominently whenever any copy of a Project Gutenberg™
work (any work on which the phrase “Project Gutenberg” appears,
or with which the phrase “Project Gutenberg” is associated) is
accessed, displayed, performed, viewed, copied or distributed:

This eBook is for the use of anyone anywhere in the United States
and most other parts of the world at no cost and with almost no
restrictions whatsoever. You may copy it, give it away or re-use it
under the terms of the Project Gutenberg License included with
this eBook or online at www.gutenberg.org. If you are not located
in the United States, you will have to check the laws of the
country where you are located before using this eBook.
1.E.2. If an individual Project Gutenberg™ electronic work is derived
from texts not protected by U.S. copyright law (does not contain a
notice indicating that it is posted with permission of the copyright
holder), the work can be copied and distributed to anyone in the
United States without paying any fees or charges. If you are
redistributing or providing access to a work with the phrase “Project
Gutenberg” associated with or appearing on the work, you must
comply either with the requirements of paragraphs 1.E.1 through
1.E.7 or obtain permission for the use of the work and the Project
Gutenberg™ trademark as set forth in paragraphs 1.E.8 or 1.E.9.
1.E.3. If an individual Project Gutenberg™ electronic work is posted
with the permission of the copyright holder, your use and distribution
must comply with both paragraphs 1.E.1 through 1.E.7 and any
additional terms imposed by the copyright holder. Additional terms
will be linked to the Project Gutenberg™ License for all works posted
with the permission of the copyright holder found at the beginning
of this work.
1.E.4. Do not unlink or detach or remove the full Project
Gutenberg™ License terms from this work, or any files containing a
part of this work or any other work associated with Project
Gutenberg™.
1.E.5. Do not copy, display, perform, distribute or redistribute this
electronic work, or any part of this electronic work, without
prominently displaying the sentence set forth in paragraph 1.E.1

with active links or immediate access to the full terms of the Project
Gutenberg™ License.
1.E.6. You may convert to and distribute this work in any binary,
compressed, marked up, nonproprietary or proprietary form,
including any word processing or hypertext form. However, if you
provide access to or distribute copies of a Project Gutenberg™ work
in a format other than “Plain Vanilla ASCII” or other format used in
the official version posted on the official Project Gutenberg™ website
(www.gutenberg.org), you must, at no additional cost, fee or
expense to the user, provide a copy, a means of exporting a copy, or
a means of obtaining a copy upon request, of the work in its original
“Plain Vanilla ASCII” or other form. Any alternate format must
include the full Project Gutenberg™ License as specified in
paragraph 1.E.1.
1.E.7. Do not charge a fee for access to, viewing, displaying,
performing, copying or distributing any Project Gutenberg™ works
unless you comply with paragraph 1.E.8 or 1.E.9.
1.E.8. You may charge a reasonable fee for copies of or providing
access to or distributing Project Gutenberg™ electronic works
provided that:
• You pay a royalty fee of 20% of the gross profits you derive
from the use of Project Gutenberg™ works calculated using the
method you already use to calculate your applicable taxes. The
fee is owed to the owner of the Project Gutenberg™ trademark,
but he has agreed to donate royalties under this paragraph to
the Project Gutenberg Literary Archive Foundation. Royalty
payments must be paid within 60 days following each date on
which you prepare (or are legally required to prepare) your
periodic tax returns. Royalty payments should be clearly marked
as such and sent to the Project Gutenberg Literary Archive
Foundation at the address specified in Section 4, “Information

about donations to the Project Gutenberg Literary Archive
Foundation.”
• You provide a full refund of any money paid by a user who
notifies you in writing (or by e-mail) within 30 days of receipt
that s/he does not agree to the terms of the full Project
Gutenberg™ License. You must require such a user to return or
destroy all copies of the works possessed in a physical medium
and discontinue all use of and all access to other copies of
Project Gutenberg™ works.
• You provide, in accordance with paragraph 1.F.3, a full refund of
any money paid for a work or a replacement copy, if a defect in
the electronic work is discovered and reported to you within 90
days of receipt of the work.
• You comply with all other terms of this agreement for free
distribution of Project Gutenberg™ works.
1.E.9. If you wish to charge a fee or distribute a Project Gutenberg™
electronic work or group of works on different terms than are set
forth in this agreement, you must obtain permission in writing from
the Project Gutenberg Literary Archive Foundation, the manager of
the Project Gutenberg™ trademark. Contact the Foundation as set
forth in Section 3 below.
1.F.
1.F.1. Project Gutenberg volunteers and employees expend
considerable effort to identify, do copyright research on, transcribe
and proofread works not protected by U.S. copyright law in creating
the Project Gutenberg™ collection. Despite these efforts, Project
Gutenberg™ electronic works, and the medium on which they may
be stored, may contain “Defects,” such as, but not limited to,
incomplete, inaccurate or corrupt data, transcription errors, a
copyright or other intellectual property infringement, a defective or

damaged disk or other medium, a computer virus, or computer
codes that damage or cannot be read by your equipment.
1.F.2. LIMITED WARRANTY, DISCLAIMER OF DAMAGES - Except for
the “Right of Replacement or Refund” described in paragraph 1.F.3,
the Project Gutenberg Literary Archive Foundation, the owner of the
Project Gutenberg™ trademark, and any other party distributing a
Project Gutenberg™ electronic work under this agreement, disclaim
all liability to you for damages, costs and expenses, including legal
fees. YOU AGREE THAT YOU HAVE NO REMEDIES FOR
NEGLIGENCE, STRICT LIABILITY, BREACH OF WARRANTY OR
BREACH OF CONTRACT EXCEPT THOSE PROVIDED IN PARAGRAPH
1.F.3. YOU AGREE THAT THE FOUNDATION, THE TRADEMARK
OWNER, AND ANY DISTRIBUTOR UNDER THIS AGREEMENT WILL
NOT BE LIABLE TO YOU FOR ACTUAL, DIRECT, INDIRECT,
CONSEQUENTIAL, PUNITIVE OR INCIDENTAL DAMAGES EVEN IF
YOU GIVE NOTICE OF THE POSSIBILITY OF SUCH DAMAGE.
1.F.3. LIMITED RIGHT OF REPLACEMENT OR REFUND - If you
discover a defect in this electronic work within 90 days of receiving
it, you can receive a refund of the money (if any) you paid for it by
sending a written explanation to the person you received the work
from. If you received the work on a physical medium, you must
return the medium with your written explanation. The person or
entity that provided you with the defective work may elect to provide
a replacement copy in lieu of a refund. If you received the work
electronically, the person or entity providing it to you may choose to
give you a second opportunity to receive the work electronically in
lieu of a refund. If the second copy is also defective, you may
demand a refund in writing without further opportunities to fix the
problem.
1.F.4. Except for the limited right of replacement or refund set forth
in paragraph 1.F.3, this work is provided to you ‘AS-IS’, WITH NO
OTHER WARRANTIES OF ANY KIND, EXPRESS OR IMPLIED,

INCLUDING BUT NOT LIMITED TO WARRANTIES OF
MERCHANTABILITY OR FITNESS FOR ANY PURPOSE.
1.F.5. Some states do not allow disclaimers of certain implied
warranties or the exclusion or limitation of certain types of damages.
If any disclaimer or limitation set forth in this agreement violates the
law of the state applicable to this agreement, the agreement shall be
interpreted to make the maximum disclaimer or limitation permitted
by the applicable state law. The invalidity or unenforceability of any
provision of this agreement shall not void the remaining provisions.
1.F.6. INDEMNITY - You agree to indemnify and hold the Foundation,
the trademark owner, any agent or employee of the Foundation,
anyone providing copies of Project Gutenberg™ electronic works in
accordance with this agreement, and any volunteers associated with
the production, promotion and distribution of Project Gutenberg™
electronic works, harmless from all liability, costs and expenses,
including legal fees, that arise directly or indirectly from any of the
following which you do or cause to occur: (a) distribution of this or
any Project Gutenberg™ work, (b) alteration, modification, or
additions or deletions to any Project Gutenberg™ work, and (c) any
Defect you cause.
Section 2. Information about the Mission
of Project Gutenberg™
Project Gutenberg™ is synonymous with the free distribution of
electronic works in formats readable by the widest variety of
computers including obsolete, old, middle-aged and new computers.
It exists because of the efforts of hundreds of volunteers and
donations from people in all walks of life.
Volunteers and financial support to provide volunteers with the
assistance they need are critical to reaching Project Gutenberg™’s
goals and ensuring that the Project Gutenberg™ collection will

remain freely available for generations to come. In 2001, the Project
Gutenberg Literary Archive Foundation was created to provide a
secure and permanent future for Project Gutenberg™ and future
generations. To learn more about the Project Gutenberg Literary
Archive Foundation and how your efforts and donations can help,
see Sections 3 and 4 and the Foundation information page at
www.gutenberg.org.
Section 3. Information about the Project
Gutenberg Literary Archive Foundation
The Project Gutenberg Literary Archive Foundation is a non-profit
501(c)(3) educational corporation organized under the laws of the
state of Mississippi and granted tax exempt status by the Internal
Revenue Service. The Foundation’s EIN or federal tax identification
number is 64-6221541. Contributions to the Project Gutenberg
Literary Archive Foundation are tax deductible to the full extent
permitted by U.S. federal laws and your state’s laws.
The Foundation’s business office is located at 809 North 1500 West,
Salt Lake City, UT 84116, (801) 596-1887. Email contact links and up
to date contact information can be found at the Foundation’s website
and official page at www.gutenberg.org/contact
Section 4. Information about Donations to
the Project Gutenberg Literary Archive
Foundation
Project Gutenberg™ depends upon and cannot survive without
widespread public support and donations to carry out its mission of
increasing the number of public domain and licensed works that can
be freely distributed in machine-readable form accessible by the
widest array of equipment including outdated equipment. Many

small donations ($1 to $5,000) are particularly important to
maintaining tax exempt status with the IRS.
The Foundation is committed to complying with the laws regulating
charities and charitable donations in all 50 states of the United
States. Compliance requirements are not uniform and it takes a
considerable effort, much paperwork and many fees to meet and
keep up with these requirements. We do not solicit donations in
locations where we have not received written confirmation of
compliance. To SEND DONATIONS or determine the status of
compliance for any particular state visit www.gutenberg.org/donate.
While we cannot and do not solicit contributions from states where
we have not met the solicitation requirements, we know of no
prohibition against accepting unsolicited donations from donors in
such states who approach us with offers to donate.
International donations are gratefully accepted, but we cannot make
any statements concerning tax treatment of donations received from
outside the United States. U.S. laws alone swamp our small staff.
Please check the Project Gutenberg web pages for current donation
methods and addresses. Donations are accepted in a number of
other ways including checks, online payments and credit card
donations. To donate, please visit: www.gutenberg.org/donate.
Section 5. General Information About
Project Gutenberg™ electronic works
Professor Michael S. Hart was the originator of the Project
Gutenberg™ concept of a library of electronic works that could be
freely shared with anyone. For forty years, he produced and
distributed Project Gutenberg™ eBooks with only a loose network of
volunteer support.

Project Gutenberg™ eBooks are often created from several printed
editions, all of which are confirmed as not protected by copyright in
the U.S. unless a copyright notice is included. Thus, we do not
necessarily keep eBooks in compliance with any particular paper
edition.
Most people start at our website which has the main PG search
facility: www.gutenberg.org.
This website includes information about Project Gutenberg™,
including how to make donations to the Project Gutenberg Literary
Archive Foundation, how to help produce our new eBooks, and how
to subscribe to our email newsletter to hear about new eBooks.

Welcome to our website – the perfect destination for book lovers and
knowledge seekers. We believe that every book holds a new world,
offering opportunities for learning, discovery, and personal growth.
That’s why we are dedicated to bringing you a diverse collection of
books, ranging from classic literature and specialized publications to
self-development guides and children's books.
More than just a book-buying platform, we strive to be a bridge
connecting you with timeless cultural and intellectual values. With an
elegant, user-friendly interface and a smart search system, you can
quickly find the books that best suit your interests. Additionally,
our special promotions and home delivery services help you save time
and fully enjoy the joy of reading.
Join us on a journey of knowledge exploration, passion nurturing, and
personal growth every day!
testbankmall.com

Solution Manual for Business Intelligence: A Managerial Perspective on Analytics, 3/E 3rd Edition. Ramesh Sharda, Dursun Delen, Efraim Turban

More Related Content

Similar to Solution Manual for Business Intelligence: A Managerial Perspective on Analytics, 3/E 3rd Edition. Ramesh Sharda, Dursun Delen, Efraim Turban (20)

Recently uploaded (20)

Solution Manual for Business Intelligence: A Managerial Perspective on Analytics, 3/E 3rd Edition. Ramesh Sharda, Dursun Delen, Efraim Turban