Decision Support Systems Development and Benefits of Business Intelligence Systems Usage
The developers and technologists of information systems design and explore decision support systems over 35 years. They emerged at the beginning of the distributed computer processing, but their history is not so straightforward and linear. That is why it is necessary a short retrospection and analy...
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| Cite this: | Decision Support Systems Development and Benefits of Business Intelligence Systems Usage / N. Marinova // Економічний вісник Донбасу. — 2010. — № 4(22). — С. 214-218. — Бібліогр.: 10 назв. — англ. |
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Marinova, N. 2011-07-08T12:05:21Z 2011-07-08T12:05:21Z 2010 Decision Support Systems Development and Benefits of Business Intelligence Systems Usage / N. Marinova // Економічний вісник Донбасу. — 2010. — № 4(22). — С. 214-218. — Бібліогр.: 10 назв. — англ. 1817-3772 https://nasplib.isofts.kiev.ua/handle/123456789/24027 [005.53:004]:338.22 The developers and technologists of information systems design and explore decision support systems over 35 years. They emerged at the beginning of the distributed computer processing, but their history is not so straightforward and linear. That is why it is necessary a short retrospection and analysis of their development to be made, before exploring the contemporary systems of such type. Key words: decision, system, development, business, benefit. Розробники і технологи інформаційних систем проектують та досліджують системи забезпечення ухвалення рішень понад 35 років. Вони з’явилися на початку розподіленої обробки даних, але їх історія не так проста і лінійна. Тому необхідно коротко проаналізувати сучасний розвиток, що й здійснено в цій статті. Ключові слова: рішення, система, розвиток, бізнес, вигода. Разработчики и технологи информационных систем проектируют и исследуют системы обеспечения принятия решений свыше 35 лет. Они появились в начале распределенной обработки данных, но их история не так проста и линейна. Поэтому необходимо короткое размышление о прошлом и анализ их развития, которое сделано в настоящей статье, перед исследованием перспектив современных систем такого типа. Ключевые слова: решение, система, развитие, бизнес, выгода. en Інститут економіки промисловості НАН України Економічний вісник Донбасу Management of Innovations Decision Support Systems Development and Benefits of Business Intelligence Systems Usage Розвиток систем забезпечення ухвалення рішень і вигоди від використання систем штучного інтелекту в бізнесі Развитие систем обеспечения принятия решений и выгоды от использования систем искусственного интеллекта в бизнесе Article published earlier |
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Decision Support Systems Development and Benefits of Business Intelligence Systems Usage |
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Decision Support Systems Development and Benefits of Business Intelligence Systems Usage Marinova, N. Management of Innovations |
| title_short |
Decision Support Systems Development and Benefits of Business Intelligence Systems Usage |
| title_full |
Decision Support Systems Development and Benefits of Business Intelligence Systems Usage |
| title_fullStr |
Decision Support Systems Development and Benefits of Business Intelligence Systems Usage |
| title_full_unstemmed |
Decision Support Systems Development and Benefits of Business Intelligence Systems Usage |
| title_sort |
decision support systems development and benefits of business intelligence systems usage |
| author |
Marinova, N. |
| author_facet |
Marinova, N. |
| topic |
Management of Innovations |
| topic_facet |
Management of Innovations |
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2010 |
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English |
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Економічний вісник Донбасу |
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Інститут економіки промисловості НАН України |
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Article |
| title_alt |
Розвиток систем забезпечення ухвалення рішень і вигоди від використання систем штучного інтелекту в бізнесі Развитие систем обеспечения принятия решений и выгоды от использования систем искусственного интеллекта в бизнесе |
| description |
The developers and technologists of information systems design and explore decision support systems over 35 years. They emerged at the beginning of the distributed computer processing, but their history is not so straightforward and linear. That is why it is necessary a short retrospection and analysis of their development to be made, before exploring the contemporary systems of such type. Key words: decision, system, development, business, benefit.
Розробники і технологи інформаційних систем проектують та досліджують системи забезпечення ухвалення рішень понад 35 років. Вони з’явилися на початку розподіленої обробки даних, але їх історія не так проста і лінійна. Тому необхідно коротко проаналізувати сучасний розвиток, що й здійснено в цій статті. Ключові слова: рішення, система, розвиток, бізнес, вигода.
Разработчики и технологи информационных систем проектируют и исследуют системы обеспечения принятия решений свыше 35 лет. Они появились в начале распределенной обработки данных, но их история не так проста и линейна. Поэтому необходимо короткое размышление о прошлом и анализ их развития, которое сделано в настоящей статье, перед исследованием перспектив современных систем такого типа. Ключевые слова: решение, система, развитие, бизнес, выгода.
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| issn |
1817-3772 |
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https://nasplib.isofts.kiev.ua/handle/123456789/24027 |
| citation_txt |
Decision Support Systems Development and Benefits of Business Intelligence Systems Usage / N. Marinova // Економічний вісник Донбасу. — 2010. — № 4(22). — С. 214-218. — Бібліогр.: 10 назв. — англ. |
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214
Економічний вісник Донбасу № 4 (22), 2010
N. Marinova
Management of innovations
I.
The developers and technologists of information systems
design and explore decision support systems over 35 years.
They emerged at the beginning of the distributed computer
processing, but their history is not so straightforward and
linear. That is why it is necessary a short retrospection and
analysis of their development to be made, before exploring
the contemporary systems of such type.
Before 1965 it was too expensive to design a broad
range information systems based on high class computers
and that is why, the big companies have accepted more
practical and effective (from cost point of view) approach
to develop Management Information Systems (MIS).
These systems centered on supporting managers by
structured, periodical reports, gathering information
mostly from accounting and transactional systems.
In the end of the 1960s there emerged in practice
so called model — oriented DSS or Decision-Making
Support System (DMSS), which have been used mainly
for supporting investing managers in their administration
of a clients’ stock portfolio. Peter Keen and Charles Stabell
are pioneers in the field of DSS.
From technological point of view, very important is
DSS designed by J. Little in 1975, called Brandaid, by which
he pointed out several criteria for designing models and
decision support systems, which are valid until today when
evaluating the contemporary DSS, e.g. robustness, ease of
control, simplicity, and completeness of relevant details.
Except by Americans, DSS conception (in French —
SIAD) is developed independently also in France by
scientists, working on the SCARABEE project (1969-1974).
In 1979 John Rockart (Harvard Business School)
published a key paper, which outlined the main ideas for
designing and developing of so called Executive
Information Systems (EIS) and Executive Support
Systems (ESS). Later, some other authors created the
theoretical range of the knowledge oriented DSS, showing
how important for development of DSS Artificial
Intelligence and Expert Systems are. The First International
Conference on DSS was held in Atlanta in 1981.
Of course, in the area of DSS have been working
many more researchers and designers whose achievements
can not be given in this paper in details, but it is important
the following remark to be done. Up to the end of 1970s are
developed a variety of interactive information systems based
on data and models supporting the managers in analyzing of
semi-structured problems but all of them were called with
the common name decision support systems. In this early
time there were considerations, that DSS could be designed
to support decision makers at every organizational level; to
support operations, financial management and strategic
decision making using spatial data, structured
multidimensional data and unstructured documents. In DSS
were applied different models, including optimization and
simulation ones and their establishment were founded
predominantly on statistical program packages.
In the early 1980s, academic researches developed
new category of software to support group decision-
making — group DSS.
Gradually EIS evolved from single user model-
oriented DSS toward data-oriented ЕIS and improved
products for relational databases. More specifically, at
the beginning of 1990s data warehousing and on-line
analytical processing technologies started expanding the
area of EIS and defined a broader category of data-
oriented decision support systems. Bill Inmon (who
first used the term “data warehouse” in literature) and
Ralph Kimball are ones of the most active supporters of
the idea for DSS, based on usage of relational database
technology. Meanwhile, the term “business intelligence”1
emerged describing a set of conceptions and methods
for improvement business decisions making through facts
supporting systems use. It could be said, that business
intelligence systems (BIS) are data-driven DSS.
In the beginning of 1990s, a main technological
revolutionary change happened — a shift from DSS
working on mainframe platforms toward DSS, based on
client/server technology. At this time, some desktop on-
line analytical processing (OLAP) tools were introduced,
too. DBMS producers realized the importance of OLAP
technology and started implementing real OLAP
capabilities into their databases. The two key technologies
— EIS and data warehousing — overlapped. In 1995,
when data warehousing and World Wide Web began to
influence the work of practitioners and researchers
working in the area of decision making support
technologies the first Web-based DSS appeared.
Today, in decision making process support are used
systems, operating on different management levels and
the most important of which are Knowledge Work
УДК [005.53:004]:338.22
N. Marinova,
PhD, D. Tsenov Academy of Economics, Svishtov, Bulgaria
DECISION SUPPORT SYSTEMS DEVELOPMENT AND BENEFITS OF BUSINESS
INTELLIGENCE SYSTEMS USAGE
1 The term “business intelligence” (BI) was proposed by Howard Dresner from Gartner Group in 1989.
215
Економічний вісник Донбасу № 4 (22), 2010
N. Marinova
Systems/Knowledge Management Systems (KWS/KMS)
and Office Automation Systems (OAS) at the level of
knowledge management, Decision Support Systems
(DSS) and Management Information Systems (MIS) at
the management level, and Executive Support Systems
(ESS) at the strategic level2.
KWS/KMS help companies to find, organize and
integrate new business knowledge. Working with
knowledge are people, who possess university degrees
and often are members of recognized professions —
engineers, doctors, lowers and scientists. In comparison
the OAS support and manage documents and the
document flow throughout the enterprise. Working with
data people (secretaries, accountants, clerks, or
managers) possess less formal modern scientific degrees
and do not create information, but they process, use,
manipulate and disseminate it.
MIS aggregate and create weekly, monthly and annual
reports about the essential operations in the company and
are oriented almost exclusively to internal (not external)
events. They serve functions of planning, controlling and
decision making at the middle management level, work with
structured questions and use routine procedures. They are
not flexible and have weak analytical capabilities. At the same
level work DSS, but they however support semi-structured,
unique and fast changing decision making utilizing internal
and external sources. DSS have significantly more analytical
power, allow users’ direct work through their user-friendly
interface and are interactive.
ESS serve the top strategic firm management. These
systems deal with non-structured decisions, they are
designed to be able to collect data from external events
but simultaneously they aggregate the information from
internal MIS and DSS. They filter, compress and track
critical business data using the most contemporary
graphic software, and less analytical models.
Throughout the years there have been designed
decision making support systems in various functional
areas, earmarked for execution of strategic, tactical and
operative business goals at a given moment, according
to the overall economic development and market
traditions3. Recently however, under conditions of the
global competition and fast changing market environment
the management puts forward new requirements about
this kind of systems in order to let the organization remain
competitive and flourishing:
—> Faster information synthesis and a more
intelligent analysis — the business environment is much
more competitive today, because organizations became
decentralized, products life cycle shortened, too. In order
to function in such environment, organizations need more
intelligent analyses and technologies to connect their
operational performance with the strategic goals;
—> More and more increasing needs for exact,
essential and timely data — today, when the information
volume increases all the time and the changes in business
environment are highly dynamic, corporative decision
making will get worse if basic data are defective,
inaccessible or obsolete. Therefore, companies want to
have well timed access to various, but reliable information
sources to make adequate decisions4;
—> A requirement for making better decisions faster
— as the main assumption for decision making is the
information, which is fast changing by nature, it is too
difficult for the business to cover and evaluate these changes.
Better decision making process demands the envelopment
and evaluation to be improved, in order to receive less wrong
and much better decisions, which support the corporative
goals. Because of the competition the opportunities for
business are extremely time sensitive and that is why, there
is a need to make not only better, but faster decisions using
quicker access to relevant information;
—> Real time working — in contemporary
conditions it becomes very necessary to establish
enterprises which could work with so called zero latency.
This means that the goods manufactured by a respective
producer have to be realized fast without using warehouses.
This could happen only by using real time systems;
—> Competitive power improvement — since e-
commerce has changed competition parameters in all
industries oriented toward production or services,
companies repeatedly seek for new technologies and new
ways for their usage in order to take possession and make
use of their sources effectively and on this basis — to
remedy their competitive situation on the market;
—> Management and staff productivity
improvement — recently the focus is shifting more toward
the management productivity in contradiction of
production effectiveness improvement only. While
managers make decisions, not goods, their productivity
is measured by quality and timeliness of these decisions.
Companies consider that managers’ decisions are more
important for organizational productivity than operative
activities automation and therefore, they look for methods
for its short-term and long-term improvement;
—> Using comprehensible models and
transformations for insight — business users want to
analyze and acquire thorough insight of their data using
more comprehensible models. They do not desire
complex statistical conceptions — they want to employ
tools for direct visualization and to obtain immediate
respond to their tasks results;
2 Laudon, K. C., Laudon, J. P., Management Information Systems: Organization and Technology in the Networked Enterprises, 6th
Edition, Prentice-Hall, ISBN 0-13-011732-3, 2000.
3 For more details about the purpose of the DSS types see: Power D. J. A Brief History of Decision Support Systems,
DSSResources.COM, version 4.1. http://DSSResources.COM/history/dsshistory.html Cited 23.09.2010.
4 Business Intelligence — THE MISSING LINK, July 2000, http://www.cherrytreeco.com.
216
Економічний вісник Донбасу № 4 (22), 2010
N. Marinova
—> The analytics as a part of a larger system —
consumers want the analytical capabilities to be built
within the systems instead of realized through additional
tools subsequently. Such improvements could be sought
mostly in the areas of data collection, generation of unique
identifiers, integration with multiple data sources, etc.5.
From all said above, one can realize, that the decisions
support systems based on information technologies are
not as new as an idea, but they have gone a “long way” of
development and improving in order to reach the
contemporary business intelligence tools and systems.
II.
Throughout the years the term Business Intelligence
significantly expanded it scope and turn to an important
aspect of the management information support. In order
to clarify this term6 many books, papers, etc. have been
written and research performed, but the most important
thing is that the development of the realizing it intelligent
technologies and tools has lead to emerging of new type
of decision support information systems — Business
Intelligence Systems (BIS).
An important advantage of BIS is that with their
assistance the decision makers can understand not only
what has happened (the main task of the MIS in the past),
but also why and what could be done. Discovering answers
of the questions why and what could be done, BIS helps
managers to drill down to the roots of the emerged
problems for preventing the appearance of such similar
matters in the future.
First BIS use too many of so called data marts7, data
warehouses (described later) and operative databases. But
meanwhile however, business intelligence activities expand
in order to include other type of data, information and
knowledge, oriented toward the future. BIS is centered
mostly on the management of external and internal
information, knowledge and the resulting intelligence to
be able to create competitive advantage related to the
achievable and measurable goals of the company. On the
other hand BIS could be viewed as a set of tools and
applications, which help the decision makers to collect,
organize, analyze, distribute and act on critical business
issues aiming to support the companies to make faster,
better and more informed business decisions.
Therefore, BIS could be defined as business
information systems, which transform selected data,
information and knowledge into specific intelligence
in order to let the decision makers to gain business
profit8. The type of BIS and the software, which is used,
depend on the situation. BIS use various analytical,
interactive and linked tools and the infrastructure of the
available databases in network environment.
We could say that BIS provide the decision makers
with the opportunity to understand (e.g. intelligence for
achieving a deep insight) of relations within the represented
facts in the form of data, information and knowledge in
order to conduct activities toward a desired and achievable
goal. They provide the decision makers with relevant data,
information and knowledge for finding problems and their
solutions.
BIS could be represented by the scheme on the fig. 1:
The source data could be internal (related to
production, consumers, suppliers and the partners) and
external (data from third parties). The database sources
are mostly relational, but there are also some text files or
electronic spreadsheets. The data fro heterogeneous
sources are transformed, aggregated and copied into the
data warehouse by usage of extracting, transforming
and loading tools (ETL). Very often the data is
transformed and validated “on the way”, and their transfer
to the data warehouse is done in the format of packets,
which are automatically scheduled. An example of such
an ETL tool is the Microsoft’s Data Transformation
Services (DTS), a part of SQL Server 2000.
The data warehouse contains read only data,
illustrating the status of the organizational information in
some specific periods of time — weekly, daily, hourly.
Important parameters of data warehouses are the quality
of data and the speed of queries sending and processing.
The data warehouse, however (when it is implemented
as a relational database) does not respond fast enough to
some complicated queries. That is why lately in order to
fill this gap, more and more often multidimensional cubes
are used (MD Cube). The MD Cub e is a complicated,
effective and specific data structure, which includes data,
aggregated data and information about security. Cubs
operate much quicker9, when replying to complicated
queries. The data in them are compressed in such a way,
that they contain ten of millions of records. The Cube
5 Emerging Trends in Business Analytics, Communications of the ACM, Volume 45, Number 8, Aug 2002, pages 45-48.
6 BI is not only a single product, a technology or a methodology — BI combines products, technologies, and methods to organize key
that management needs to improve profit and performance. Williams S., Williams N. The Profit Impact of Business Intelligence. Mogran
Kaufmann Publishers, San Francisco, 2007. p. 2. ISBN-13: 978-0-12-372499-1.
7 These are special repositories for data, containing information of a specific functional area, which serve separate organizational units
in the enterprise.
8 Thierauf R. J., Effective Business Intelligence Systems, Quorum Books, Westport, Connecticut, London, ISBN 1-56720-370-1, page
23, 2001.
9 From an architectural point of view the multidimensional cube is also a type of database with multidimensional architecture (in the
references it is also known as OLAP database) and it is a type of fast working memory. On fig. 1 the corporate data warehouse is illustrated
as a combination of two types of architectures — a relational database and OLAP database. But from a conceptual point of view it can be
implemented as a relational database, OLAP database or as a combination of both. For more details see, for example: Vitt E., Luckevich M.,
Misner S., Business Intelligence: Making Better Decisions Faster, Microsoft Press, ISBN 0-7356-1627-2, page 62, 2002.
217
Економічний вісник Донбасу № 4 (22), 2010
N. Marinova
updating very often is done during the night as a part of
the ETL package work.
There is quite a large variety of standard applications
in the end-user tools, but there could be created some
specific ones when needed. The customers’ applications
operate in several areas:
1. OLAP — in the on-line analytical processing the
end-user has direct/on-line access to the cube through
analytical software, installed on his PC. The free browsing
in information allows spontaneous actions, which make
easy tracking the trends and relations;
2. Statistic/live reports — the statistical reports
represent an information insight, arranged preliminary in
a specific way — for example, the sales during a month
in regions. The live reports allow the end-users
interactively to manipulate the information and to reach
greater details;
3. Balanced scorecards — they emphasize on the
frequent and timely measurement the individual or team
performance to key financial and non-financial aims;
4. Budgeting/forecasting — BI budgeting offers
advantages as: better forecasting, faster aggregation and
possibility to analyze up till a minute aggregations, by
using the reach capabilities of the OLAP tools;
5. Data mining — the aim of these tools is pattern
recognition in data and relations which are not obvious
for the simpler analytical methods;
6. Exceptions and notifications — the modern
systems for exceptions and notifications allow the end-
users or managers to connect the events (when there is
a registered event beyond the limits of some key
performance measurements) with some appropriate
notifications;
7. Process input — in the past the people have
transferred the information from a process to another
process. Today an automated system for purchasing can
receive information directly from BIS, in order to create the
basis of a made analysis the necessary quantity, to determine
what is on the production floor of purchases, etc.
Recently the development and implementation of
BIS includes use of combination of techniques and
technologies. These processes must be correctly planned
and conducted, in order to be really effective in appropriate
data information and knowledge and their resulting
intelligence acquisition as well as making managerial
decisions on their basis.
The development and implementation of BIS contain
the following four basic components:
• Usage of the working recent information systems
as a foundation for upgrading them with new BI modules
— the recent IS, which could be upgraded in this way
and developed to BIS are DSS, EIS, OLAP and KMS.
These systems provide an opportunity to the decision
makers for a data, information and knowledge access in
ways, which were not possible in the past, in order to let
them better understand the company’s operations, which
necessary for answering the global competition today
and in the future;
• Usage of methods for finding of the knowledge
(data mining) and BI methods and software for better
understanding of all operations of the company, now and
in the future — appropriate software is used, in order to
collect data, information and knowledge and to develop
the necessary intelligence and share the results with other
people. Today there exists a large number of software
packages, which meet the needs of the decision makers
for operative BI and only the concrete circumstances
determine which package should be selected and used;
• Establishment of effective data warehouses and
computer systems working in real time, where the focus is
on many factors, related to Internet, Intranet and Extranet
— this component includes establishment of an appropriate
infrastructure for the data, information and knowledge,
which is related with data marts, data warehouses and
operative databases. Normally, before BIS to start working
effectively using some selected software, a large quantity
of aged and/or real time data, information and knowledge
must be available in order to be resolved/explored current
or future problems/opportunities;
• Usage in highest degree a computer network
Fig. 1. A conceptual scheme of a business intelligence system.
218
Економічний вісник Донбасу № 4 (22), 2010
N. Marinova
processing, related to e-commerce as a way of doing
business with company’s customers and suppliers — the
forth component has the capability to change the way in
which the companies work with their customers,
suppliers and employees. If it is applied correctly, the
intelligent network processing could help companies to
simplify significantly their operations, because it allows
companies’ information systems to “talk” to each other.
And e-commerce provides an opportunity to businesses
to optimize their daily operations.
***
In conclusion there could be said, that the
establishment of BI environment and implementation of
BIS usually costs millions of dollars for organizations
beginning such initiative. This step requires new
technologies to be considered, some additional tasks to
be performed, roles and responsibilities to be exchanged,
and applications for analysis and decision support with
acceptable quality to be provided.10 But the properly
developed and implemented BIS ensures a number of
advantages — material (increasing the volume of sales,
increasing the profit, etc.) and non-material (for example,
improvement of the organization reputation and image,
etc.), which are hardly measurable in monetary value.
In spite of the advantages, however, if BIS initiatives
could not be linked to specific problems and strategic
goals of the organization, they would not be approved by
top management. But as we know, the main aim for BIS
development and BI tools usage is to provide new
intelligent ways for decision making and effective
management in order to keep the organization competitive
in today’s fast changing market environment.
References
1. Business Intelligence — THE MISSING LINK,
July 2000, http://www.cherrytreeco.com. 2. Emerging
Trends in Business Analytics, Communications of the
ACM, Volume 45, Number 8, Aug 2002, pages 45-48.
3. Larissa T. Moss, Shaku Atre, Business Intelligence
Roadmap: The Complete Project Lifecycle for Decision-
Support Applications, Addison Wesley, ISBN: 0-201-
78420-3, 2003. 4. Laudon K. C., Laudon J. P.,
Management Information Systems: Organization and
Technology in the Networked Enterprises, 6th Edition,
Prentice-Hall, ISBN 0-13-011732-3, 2000. 5. Loshin D.
Business Intelligence, The Savvy Manager’s Guide,
Getting Onboard with Emerging IT. Mogran Kaufmann
Publishers, San Francisco, 2003. ISBN-13: 978-1-55860-
916-7. 6. Power, D.J. A Brief History of Decision Support
Systems, DSSResources.COM, http://
DSSResources.COM/history/dsshistory.html, version
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Intelligence Systems, Quorum Books, Westport,
Connecticut, London, ISBN 1-56720-370-1, 2001.
8. Vitt E., Luckevich M., Misner S., Business
Intelligence: Making Better Decisions Faster, Microsoft
Press, ISBN 0-7356-1627-2, 2002. 9. Williams S.,
Williams N. The Profit Impact of Business Intelligence.
Mogran Kaufmann Publishers, San Francisco, 2007.
ISBN-13: 978-0-12-372499-1. 10. Черняк Л., Что
Business Intelligence предлагает бизнесу, сп. Откры-
тые системы, бр. 4, 23.04.2003 г.
Marinova N. Decision Support Systems
Development and Benefits of Business Intelligence
Systems Usage
The developers and technologists of information
systems design and explore decision support systems
over 35 years. They emerged at the beginning of the
distributed computer processing, but their history is not
so straightforward and linear. That is why it is necessary
a short retrospection and analysis of their development
to be made, before exploring the contemporary systems
of such type.
Key words: decision, system, development, business,
benefit.
Maринова Н. Розвиток систем забезпечення
ухвалення рішень і вигоди від використання си-
стем штучного інтелекту в бізнесі
Розробники і технологи інформаційних систем
проектують та досліджують системи забезпечення ух-
валення рішень понад 35 років. Вони з’явилися на
початку розподіленої обробки даних, але їх історія
не так проста і лінійна. Тому необхідно коротко
проаналізувати сучасний розвиток, що й здійснено
в цій статті.
Ключові слова: рішення, система, розвиток,
бізнес, вигода.
Maринова Н. Развитие систем обеспечения
принятия решений и выгоды от использования
систем искусственного интеллекта в бизнесе
Разработчики и технологи информационных сис-
тем проектируют и исследуют системы обеспечения
принятия решений свыше 35 лет. Они появились в на-
чале распределенной обработки данных, но их история
не так проста и линейна. Поэтому необходимо короткое
размышление о прошлом и анализ их развития, кото-
рое сделано в настоящей статье, перед исследованием
перспектив современных систем такого типа.
Ключевые слова: решение, система, развитие,
бизнес, выгода.
Received by the editors: 26.09.2010
and final form in 01.12.2010
10 60% of BI projects end up with abandon or failure, due to the non-adequate planning, missed tasks, not met deadlines, bad
management and so on — source: Larissa T. Moss, Shaku Atre, Business Intelligence Roadmap: The Complete Project Lifecycle for
Decision-Support Applications, Addison Wesley, ISBN: 0-201-78420-3, 2003.
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