Principles and applications of business intelligence research:
"This book provides the latest ideas and research on advancing the understanding and implementation of business intelligence within organizations"--Provided by publisher
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| Format: | Buch |
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| Sprache: | English |
| Veröffentlicht: |
Hershey, Pa.
Business Science Reference
2013
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis Inhaltsverzeichnis |
| Zusammenfassung: | "This book provides the latest ideas and research on advancing the understanding and implementation of business intelligence within organizations"--Provided by publisher |
| Beschreibung: | Enth. 20 Beitr.. - Includes bibliographical references and index |
| Beschreibung: | XXIII, 333 S. Ill., graph. Darst. |
| ISBN: | 9781466626508 9781466627123 |
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Datensatz im Suchindex
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| adam_text | Titel: Principles and applications of business intelligence research
Autor: Herschel, Richard T
Jahr: 2013
Detailed Table of Contents
Preface..................................................................................................................................................xv
Section 1
Organizational Issues
Chapter 1
Using Business Intelligence in College Admissions: A Strategic Approach
W O. Dale Amburgey, Saint Joseph s University, USA
John C. Yi, Saint Joseph s University, USA
Higher education often lags behind industry in the adoption of new or emerging technologies. As com-
petition increases among colleges and universities for a diminishing supply of prospective students, the
need to adopt the principles of business intelligence becomes increasingly more important. Data from
first-year enrolling students for the 2006-2008 fall terms at a private, master s-level institution in the
northeastern United States was analyzed for the purpose of developing predictive models. A decision
tree analysis, a neural network analysis, and a multiple regression analysis were conducted to predict
each student s grade point average (GPA) at the end of the first year of academic study. Numerous
geodemographic variables were analyzed to develop the models to predict the target variable. The overall
performance of the models developed in the analysis was evaluated by using the average square error
(ASE). The three models had similar ASE values, which indicated that any of the models could be used
for the intended purpose. Suggestions for future analysis include expansion of the scope of the study to
include more student-centric variables and to evaluate GPA at other student levels.
Chapter 2
Anticipatory Standards Development and Competitive Intelligence...................................................17
Francoise Bousquet, ZFIB Conseil, France
Vladislav V. Fomin, Vytautas Magnus University, Lithuania; Turiba School of Business
Administration, Latvia
Dominique Drillon, La Rochelle Business School, France
More and more companies operate today in a worldwide market under conditions of globalization,
increased complexity, and competition. In such an environment, business decisions need to be made
quickly yet intelligent, substantiated by the most salient and relevant information available. Under the
global competition, with a diligent and measured manner, many companies are increasingly treating
business like an economic war. Enterprises are methodically monitoring and investigating their competi-
tors, while deploying all the resources they have at their disposal in order to beat their current or future
rivals. Competitive Intelligence (CI) has become the latest weapon in the world war of economies .
This paper contributes to the growing body of literature on competitive intelligence by synthesizing
knowledge stemming from many years of experience in the standardization arena. The authors aim to
show how, in the economic war, engaging in committee-based standards development may be used for
winning the competition battle.
Chapter 3
Champion for Business Intelligence: SMART Goals for Business Focused and Financially Backed
Results...................................................................................................................................................31
Irina Dymarsky, Purdue Pharma, USA
Although Gartner s EXP 2006 CIO Survey ranked Business Intelligence (BI) as the top technology
priority, BI projects face tough competition from other projects in IT portfolios promising more tangible
financial returns (Wu Weitzman, 2006) Two major hurdles that prevent BI projects from shining in
portfolios are vague requirements and weak benefits calculations. Both can be addressed by examining
and learning from a number of case studies that prove tangible ROI on BI solutions when scoped and
designed with a focus on specific, measurable, achievable, results-oriented, and time bound SMART
business goals. In order for BI projects to compete in IT portfolios based on financial measures, like
ROI, BI champions need to approach BI requirements gathering with the goal of addressing a specific
business problem as well as employ standard ways of calculating BI benefits post project go live. By
examining common failures with BI requirements and case studies which demonstrate how successful
BI implementations translate into tangible benefits for the organization, BI champions develop a toolkit
of tips, tricks, and lessons learned for successful requirements gathering, design, implementation, and
measure of business results on BI initiatives.
Chapter 4
Enterprise Intelligence: A Case Study and the Future of Business Intelligence...................................47
Joseph Morabito, Stevens Institute of Technology, USA
Edward A. Stohr, Stevens Institute of Technology, USA
Yegin Gene, Stevens Institute of Technology, USA
This paper examines the key issues associated with current and future implementations of business intel-
ligence (BI). The authors review the literature and discover both the growing importance and emerging
issues associated with BI. The issues are further examined with an exploratory, but detailed, case study
of organizations from a variety of industries, yielding a series of lessons learned. The authors find that
organizations are rapidly moving to an enterprise perspective on BI, but in an unsystematic way. The
authors present a prescription for the future of BI called enterprise intelligence (El). EI is described in
a framework that combines elements of hierarchy theory, organization modeling, and intellectual capital.
Chapter 5
Business Intelligence Competency Centers: Centralizing an Enterprise Business Intelligence
Strategy.................................................................................................................................................68
Daniel O Neill, Avon Products Inc., USA
Enterprises today continue to invest in business intelligence (BI) initiatives with the hope of providing
a strategic advantage to their organizations. Many of these initiatives are supporting the tactical goals
of individual business units and not the strategic goals of the enterprise. Although this decentralized
approach provides short term gains, it creates an environment where information silos develop and the
enterprise as a whole struggles to develop a single version of the truth when it comes to providing stra-
tegic information. Enterprises are turning toward a centralized approach to BI which aligns with their
overall strategic goals. At the core of the centralized approach is the business intelligence competency
center (BICC). This paper details why the centralized BICC approach should be considered an essential
component of all enterprise BI initiatives. Examining case studies of BICC implementations details the
benefits realized by real world companies who have taken this approach. It is also important to provide
analysis of the two BI approaches in the areas of BI process and BI technology/data and people relations.
The findings indicate the benefits of the centralized BICC outweigh the deficiencies of the decentralized
approach.
Chapter 6
BI s Impact on Analyses and Decision Making Depends on the Development of Less Complex
Applications .........................................................................................................................................83
Robert Sawyer, I.B.I.S. Inc., USA
This paper addresses where BI developers have failed to create applications suited for the common
end-user and provide a conceptual roadmap to address these shortfalls. It is argued that BI s impact
on analyses and decision-making depends on the development of less complex applications. Research
conducted for this paper finds that BI lacks a commo n definition and standard, that BI tools are too
complex for the common user, and that a shortage of analytical literacy relevant to BI among business
professionals is a barrier to BI adoption. The paper suggests that until BI analysis tools become more
human-centric, design-oriented and less from a technology-centric, engineering-oriented perspective ,
BI will continue to fail in its objective to routinely improve business decision-making.
Chapter 7
Discovering Business Intelligence from the Subjective Web Data.......................................................96
Ranjit Bose, University of New Mexico, USA
The online word-of-mouth behavior that exists today in the Web represents new and measurable sources
of information. The automated discovery or mining of consumer opinions from these sources is of great
importance for marketing intelligence and product benchmarking. Techniques are now being developed
to effectively and easily mine the consumer opinions from the Web data and to timely deliver them to
companies and individual consumers. This study investigates this emerging field named opinion min-
ing in terms of what it is, what it can do, and how it could be used effectively for business intelligence
(BI). A rigorous review of the research literature on opinion mining is conducted to explore its current
state, issues and challenges for its use in developing business applications for competitive advantage.
The study aims to assist business managers to better understand the current opportunities and challenges
in using opinion mining for deriving BI. Future research directions for further development of the field
are also identified.
Chapter 8
Business Intelligence Enhances Strategic, Long-Range Planning in the Commercial Aerospace
Industry...............................................................................................................................................112
David Ellis, Boeing, USA
The world s largest aircraft manufacturers like Boeing and Airbus have traditionally been dominant in
the commercial aerospace industry, but due to the rise of several smaller commercial aircraft companies
and in spite of air travel increasing each year, it will be paramount for Boeing and Airbus to thoroughly
understand past and current market conditions and be able to combine their understanding with the proper
analytical tools to anticipate the market demands of the future if they are to remain the world leaders in
their industry. This paper presents a discussion of industry factors such as airline routes, past passenger
demands in different regions of the world and the sizes and types of aircraft that were required to sup-
port those demands, and more importantly, how analysis of that information is integral to the projection
of future demands within the commercial aerospace market which will facilitate Boeing and Airbus
positioning themselves to provide their airline customers with the right product at the right time.
Chapter 9
Performance Management through Societal Performance Indicators ...............................................125
Joe White, Technical Consultant, USA
Performance management is tied to external forces and stakeholders whose assessment of performance
is more focused on societal outcomes than purely financial outcomes. Government, corporate, and even
personal performance measurement should take into account societal indicators that link these disparate
yet intertwined spheres of influence. New initiatives in both government and commercial sectors are
bringing greater understanding of how societal indicators can measure performance. This paper highlights
how societal indicators are used to measure performance in corporate and government sectors. Corporate
societal indicators are explored primarily though literary research. Government societal indicators are
explored through an examination of the EPA and Superfund program. The paper demonstrates that there
is synergy between corporate, government, and personal government performance measures and how
business intelligence tools are making these relationships more transparent.
Chapter 10
Business Intelligence Should be Centralized.....................................................................................139
Brian Johnson, Himalayan International Institute, USA
The implementation of BI into the business strategy and culture is laden with many potential points that
could result in failure of the initiative, leaving BI to be underdeveloped and a source of wasted resources
for the company. Due to the unique nature of BI in the business space, properly setting up BI within
the organizational structure from the onset of integration minimizes the impact of the most common
hurdles to BI implementation. Many companies choose to mitigate these problems by using a centralized
approach by building a Center of Excellence, but their place in the company s organizational structure
needs to be well-defined and properly empowered to be effective. This paper also reviews how the con-
cept of centralization is defined, how it relates to the implementation of BI, and how it can effectively
in overcome the common implementation hurdles.
Chapter 11
The Future Talent Shortage Will Force Global Companies to use HR Analytics to Help Manage and
Predict Future Human Capital Needs ................................................................................................153
Carey W. Worth, Consultant, USA
During the recent recession the number of jobs lost has been widely publicized. However, lurking among
this obvious and simple metric of how human capital is involved in the workforce, there is the need
to analyze and predict future talent. As economic conditions are slow to improve, decisions to simply
cut the traditional costs, benefits, compensation and headcount are no longer enough. Companies have
already started using business intelligence (BI) to transform and maximize the potential of their human
capital. The use of human capital based business intelligence (BI) has increasingly become one of the
vital strategic components for world-class companies. This paper will focus on why companies should
use analytics (a subset of Business Intelligence (BI)) to transform and maximize the potential of their
human capital.
Section 2
Analytic Issues
Chapter 12
Intelligent Analytics: Integrating Business Intelligence and Web Analytics......................................166
Lakshmi S. Iyer, The University of North Carolina at Greensboro, USA
Rajeshwari M. Raman, Market America, USA
Organizations use web analytic tools and technologies to measure, collect, analyze, and report web usage
data to help optimize websites. Traditionally, most of this data tends to be non-transactional and non-
identifiable. In this regard, there has not been much integration with transactional data that is collected,
stored, analyzed, and reported through Business Intelligence (BI). Emerging trends in web analytics
provide organizations the ability to aggregate and analyze web analytics data with transactional data to
provide valuable insights for building better customer relationship strategies. In this paper, the authors
give an overview of web analytics tools, key players, new technology trends and capabilities to integrate
web analytics with BI so organizations can leverage intelligent analytics for new marketing initiatives.
While the benefits are significant, there are some challenges associated with the integration and a few
possible solutions to address.
Chapter 13
Strategies for Improving the Efficacy of Fusion Question Answering Systems................................181
Jose Antonio Robles-Flores, ESAN University, Peru
Gregory Schymik, Arizona State University, USA
Julie Smith-David, Arizona State University, USA
Robert St. Louis, Arizona State University, USA
Web search engines typically retrieve a large number of web pages and overload business analysts with
irrelevant information. One approach that has been proposed for overcoming some of these problems is
automated Question Answering (QA). This paper describes a case study that was designed to determine
the efficacy of QA systems for generating answers to original, fusion, list questions (questions that have
not previously been asked and answered, questions for which the answer cannot be found on a single
web site, and questions for which the answer is a list of items). Results indicate that QA algorithms are
not very good at producing complete answer lists and that searchers are not very good at constructing
answer lists from snippets. These findings indicate a need for QA research to focus on crowd sourcing
answer lists and improving output format.
Section 3
Technology Issues
Chapter 14
Test-Driven Development of Data Warehouses..................................................................................200
Sam Schutte, Unstoppable Software, Inc., USA
Thilini Ariyachandra, Xavier University, USA
Mark Frolick, Xavier University, USA
Test-driven development is a software development methodology that has recently gained a great deal
of traction in the software development community. It focuses on creating software-based test cases that
define the business requirements of an application before beginning the coding of the application itself.
This paper proposes that test-driven development could be a useful methodology for data warehouse
projects, in that it could help team members avoid some of the major pitfalls of data warehousing, and
result in a higher-quality end product.
Chapter 15
Uncovering Actionable Knowledge in Corporate Data with Qualified Association Rules................210
Nenad Jukic, Loyola University Chicago, USA
Svetlozar Nestorov, University of Chicago, USA
Miguel Velasco, University of Minnesota, USA
Jami Eddington, Oklahoma State University, USA
Association rules mining is one of the most successfully applied data mining methods in today s business
settings (e.g. Amazon orNetflix recommendations to customers). Qualified association rules mining is
an extension of the association rules data mining method, that uncovers previously unknown correla-
tions that only manifest themselves under certain circumstances (e.g. on a particular day of the week),
with the goal of improving action results, e.g. turning an underperforming campaign (spread too thin
over the entire audience) into a highly targeted campaign that delivers results. Such correlations have
not been easily reachable using standard data mining tools so far. This paper describes the method for
straightforward discovery of qualified association rules and demonstrates the use of qualified associa-
tion rules mining on an actual corporate data set. The data set is a subset of a corporate data warehouse
for Sam s Club, a division of Wal-Mart Stores, INC. The experiments described in this paper illustrate
how qualified association rules supplement standard association rules data mining methods and provide
additional information which can be used to better target corporate actions.
Chapter 16
10 Principles to Ensure Your Data Warehouse Implementation is a Failure......................................230
Adam Hill, The Nielsen Company USA
Thilini Ariyachandra, Xavier University, USA
Mark Frolick, Xavier University, USA
Demand for business intelligence solutions continues to grow in the industry at record rates to combat
competitive pressures and to attain business agility. Still organizations continue to struggle on how to
implement successful business intelligence solutions. Despite its growing popularity and maturity as a
field, it appears that organizations follow key guidelines that ensure the failure of their business intel-
ligence implementation. This paper highlights ten major principles that organizations follow to ensure
the failure of their BI solution and in so doing describes how to avoid BI failure in terms of strategy
and design, implementation management and communication, and technology and resource investment
for BI solutions.
Chapter 17
Business Intelligence Conceptual Model...........................................................................................241
Fletcher H. Glancy, Lindenwood University, USA
Surya B. Yadav, Texas Tech University, USA
A business intelligence conceptual model (BISCOM) is proposed as a process-focused design theory
for developing, understanding, and evaluating business intelligence (BI) systems. Previous work has
concentrated on subsets of the BI systems, use of BI tools, and specific business functional area require-
ments. BISCOM provides a unified and comprehensive design theory that integrates and synthesizes
existing research. It extends existing research by proposing functionality that does not currently exist in
BI systems. The BISCOM is validated through descriptive methods that demonstrate the model utility
and through prototype creation to demonstrate the need for BISCOM.
Chapter 18
Mitigating Risk: Analysis of Security Information and Event Management......................................261
Ken Lozito, GSK, USA
Business Intelligence (BI) has often been described as the tools and systems that play an essential role in
the strategic planning process of a corporation. The application of BI is most commonly associated with
the analysis of sales and stock trends, pricing and customer behavior to inform business decision-making.
There is a growing trend in utilizing the tools and processes used in the analysis of data and applying
them to security event management. Security Information and Event Management (SIEM) has emerged
within the last 10 years providing a centralized source to enable both real-time and deep level analysis
of historical event data to drive security standards and align IT resources in a more efficient manner.
Chapter 19
IT and Business Can Succeed in BI by Embracing Agile Methodologies..........................................270
Alex Gann, BAE Systems, USA
While the potential benefits from BI are vast, organizations have struggled to successfully deploy it. BI
applies myriad advanced techniques, performed by the firm s Information Technology (IT) group, to
fulfill the reporting, analysis, and decision-support needs of the Lines of Business. Two of the greatest
challenges in BI are accurately and continuously communicating requirements from the business to IT
and quickly yet affordably delivering the requested functionality from IT to the business. Companies
can overcome these challenges by embracing a prescribed set of Agile development methodologies for
BI. This paper examines the history of selected systems development approaches, weighs the advantages
and disadvantages of prevailing practices, and ultimately recommends a path forward to succeeding in
BI through the application of Agile methodologies.
Chapter 20
Agile Development in Data Warehousing..........................................................................................286
Nayem Rahman, Intel Corporation, USA
Dale Rutz, Intel Corporation, USA
Shameem Akhter, Western Oregon University, USA
Traditional data warehouse projects follow a waterfall development model in which the project goes
through distinct phases such as requirements gathering, design, development, testing, deployment,
and stabilization. However, both business requirements and technology are complex in nature and the
waterfall model can take six to nine months to fully implement a solution; by then business as well
as technology has often changed considerably. The result is disappointed stakeholders and frustrated
development teams. Agile development implements projects in an iterative fashion. Also known as the
sixty percent solution, the agile approach seeks to deliver more than half of the user requirements in
the initial release, with refinements coming in a series of subsequent releases which are scheduled at
regular intervals. An agile data warehousing approach greatly increases the likelihood of successful
implementation on time and within budget. This article discusses agile development methodologies in
data warehousing and business intelligence, implications of the agile methodology, managing changes
in data warehouses given frequent change in business intelligence (BI) requirements, and demonstrates
the impact of agility on the business.
Compilation of References...............................................................................................................301
About the Contributors....................................................................................................................322
Index...................................................................................................................................................330
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| genre | 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content |
| genre_facet | Aufsatzsammlung |
| id | DE-604.BV042736654 |
| illustrated | Illustrated |
| indexdate | 2024-07-10T07:08:32Z |
| institution | BVB |
| isbn | 9781466626508 9781466627123 |
| language | English |
| lccn | 2012029158 |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-028167608 |
| oclc_num | 923734592 |
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| owner | DE-91G DE-BY-TUM |
| owner_facet | DE-91G DE-BY-TUM |
| physical | XXIII, 333 S. Ill., graph. Darst. |
| publishDate | 2013 |
| publishDateSearch | 2013 |
| publishDateSort | 2013 |
| publisher | Business Science Reference |
| record_format | marc |
| spelling | Principles and applications of business intelligence research Richard Herschel [ed.] Hershey, Pa. Business Science Reference 2013 XXIII, 333 S. Ill., graph. Darst. txt rdacontent n rdamedia nc rdacarrier Enth. 20 Beitr.. - Includes bibliographical references and index "This book provides the latest ideas and research on advancing the understanding and implementation of business intelligence within organizations"--Provided by publisher Business intelligence Wirtschaftsspionage (DE-588)4139137-8 gnd rswk-swf 1\p (DE-588)4143413-4 Aufsatzsammlung gnd-content Wirtschaftsspionage (DE-588)4139137-8 s DE-604 Herschel, Richard T. 1950- Sonstige (DE-588)172872146 oth Erscheint auch als Online-Ausgabe 978-1-466-62681-2 DE-601 pdf/application http://www.gbv.de/dms/zbw/720059798.pdf Inhaltsverzeichnis HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028167608&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Principles and applications of business intelligence research Business intelligence Wirtschaftsspionage (DE-588)4139137-8 gnd |
| subject_GND | (DE-588)4139137-8 (DE-588)4143413-4 |
| title | Principles and applications of business intelligence research |
| title_auth | Principles and applications of business intelligence research |
| title_exact_search | Principles and applications of business intelligence research |
| title_full | Principles and applications of business intelligence research Richard Herschel [ed.] |
| title_fullStr | Principles and applications of business intelligence research Richard Herschel [ed.] |
| title_full_unstemmed | Principles and applications of business intelligence research Richard Herschel [ed.] |
| title_short | Principles and applications of business intelligence research |
| title_sort | principles and applications of business intelligence research |
| topic | Business intelligence Wirtschaftsspionage (DE-588)4139137-8 gnd |
| topic_facet | Business intelligence Wirtschaftsspionage Aufsatzsammlung |
| url | http://www.gbv.de/dms/zbw/720059798.pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=028167608&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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Inhaltsverzeichnis