Description
Every business is dynamic in nature and is affected by various external and internal factors. These factors include external market conditions, competitors, internal restructuring and re-alignment, operational optimization and paradigm shifts in the business itself.
BUSINESS INTELLIGENCE TOOLS FOR DATA ANALYSIS
AND DECISION MAKING
DEJAN ZDRAVESKI
*
IGOR ZDRAVKOSKI
**
Abstract
Every business is dynamic in nature and is affected by various external and internal factors. These factors
include external market conditions, competitors, internal restructuring and re-alignment, operational
optimization and paradigm shifts in the business itself. New regulations and restrictions, in combination with the
above factors, contribute to the constant evolutionary nature of compelling, business-critical information the
kind of information that an organization needs to sustain and thrive.
!usiness intelligence "#!$%& is broad term that encapsulates the process of gathering information pertaining to
a business and the market it functions in. This information when collated and analyzed in the right manner, can
provide vital insights into the business and can be a tool to improve efficiency, reduce costs, reduce time lags
and bring many positive changes. ' business intelligence application helps to achieve precisely that.
(uccessful organizations maximize the use of their data assets through business intelligence technology. The first
data warehousing and decision support tools introduced companies to the power and benefits of accessing and
analyzing their corporate data. !usiness users at every level found new, more sophisticated ways to analyze and
report on the information mined from their vast data warehouses.
)hoosing a !usiness $ntelligence offering is an important decision for an enterprise, one that will have a
significant impact throughout the enterprise. The choice of a !$ offering will affect people up and down the
chain of command "senior management, analysts, and line managers& and across functional areas "sales,
finance, and operations&. $t will affect business users, application developers, and $T professionals.
!$ applications include the activities of decision support systems "*((&, +uery and reporting, online analytical
processing ",-'.&, statistical analysis, forecasting, and data mining. 'nother way of phrasing this is that !$
applications take data that is generated by the operations of an enterprise and translate that data into relevant
and useful information for consumption by people throughout the enterprise.
Keywords: !usiness intelligence, application, decision making, knowledge, data mining, data warehouse
Intro!ct"on
The final decades of the 20th century and the beginning of the 21st have been marked by a
staggering proliferation of information and communication technologies throughout the
industrialized world. Not only do globalization trends bring a turbulent and most often unequal
competitive environment they also propagate waves of !managerial imperatives" # such as total
quality$ reengineering and integrated systems # that e%ert tremendous pressure on organizations
wanting not only to survive but to succeed. &n addition to performance and effectiveness global
organizations are asked to display ethical social and environmental responsibility. This entire conte%t
makes the task of managing information a formidable challenge.
't present information management is seen as one of the biggest challenges characterizing
today(s corporate conte%t. ' combination of constant technological innovation and increasing
competitiveness makes the management of information a difficult task one which requires decision)
making processes that are built on reliable and timely information gathered from internal and
e%ternal sources. 'lthough the volume of information available is increasing this does not
automatically mean that people are able to derive value from it. &n the &T field after years of
significant investments to create technological platforms that support all business processes
**
+h, -aculty of .conomics)+rilep)/acedonia 0e)mail1 zigor2002yahoo.com3.
912 Challenges of the Knowledge Society. Economy
(processes that are “reengineered” and “integrated”) and that strengthen the efficiency of the
operational structure (after undergoing “quality” programs), organizations are supposed to have
reached a point where the implementation of IT solutions for strategic decision-maing processes
!ecomes possi!le and necessary" This conte#t e#plains the emergence of the area generally nown as
“!usiness intelligence” ($I), seen as an answer to current needs in terms of information for strategic
decision-maing through intensive use of information technology (IT)"
Definition of Business intelligence
The literature review of $I reveals few studies" %ost of the articles are conceptual" &hat's
more, throughout the literature, meets the traditional “separation” !etween technical and managerial
aspects, outlining two !road patterns
(
" The technological approach, which prevails in most studies,
presents $I as a set of tools that support the storage and analysis of information" This encompasses a
!road category of applications and technologies for gathering, storing, analyzing, and providing
access to data to help enterprise users mae !etter !usiness decisions" Those $I tools include decision
support systems, query and reporting, online analytical processing ()*+,), statistical analysis,
forecasting and data mining" The focus is not on the process itself, !ut on the technologies that allow
the recording, recovery, manipulation and analysis of information" -ophisticated use of warehoused
data occurs when advanced data mining techniques are applied to change data into information" .ata
mining is the utilization of mathematical and statistical applications that process and analyze data"
%athematics refers to equations or algorithms that process data to discover patterns and relationships
among varia!les" -tatistics generally shed light on the ro!ustness and validity of the relationships that
e#ist in the data mining model" *eading methods of data mining include regression, segmentation
classification, neural networs, clustering and affinity analysis" The synergy created !etween data
warehousing and data mining allows nowledge seeers to leverage their massive data assets, thus
improving the quality and effectiveness of their decisions" The growing requirements for data mining
and real time analysis of information will !e a driving force in the development of new data
warehouse architectures and methods and, conversely, the development of new data mining methods
and applications"
In short, $I is a wide set of tools and applications for gathering, consolidation, analysis and
dissemination aiming at to improve the power to decision process" The components of !usiness
intelligence that focus in collect and consolidation can involve data management software's to access
data varia!les, e#tract, transform and load tools that also enhance data access and storage in a data
warehouse or data mart" In the steps of analysis and distri!ution, each time more different products
are launched and integrated with o!/ective to tae care of the different use of the information" These
products can include the creation of reports, the fine-tuned dash!oards containing customized
performance indicators visually rich presentations using gauges, maps, charts, and other graphical
elements to show multiple results together, the generation of )*+, cu!es and the data mining
software's to discover information hidden within valua!le data assets, using advanced mathematical
and statistical techniques, can uncover veins of surprising, golden insights in a mountain of factual
data" 0igure ( presents a proposal of $I architecture, distri!uting the different technologies and
applications argued in function of its main contri!ution in each one of the steps in the $I process"
The managerial approach sees $I as a process in which data from inside and outside the
company are integrated in order to generate information relevant to the decision-maing process" The
role of $I here is related to the whole informational environment and !y which operational data
gathered from transactional systems and e#ternal sources can !e analyzed to reveal the “strategic”
!usiness dimensions" 0rom this perspective emerge concepts such as the “intelligent company”1 one
that uses $I to mae faster and smarter decisions than its competitors" ,ut simply, “intelligence”
entails the reduction of a huge volume of data into nowledge through a process of filtering,
(
+ltosoft corporation, $ringing !usiness intelligence to !usiness operations, %arch 2334"
913
analyzing and reporting information. The explanation of how companies acquire “intelligence”
would lie in the data-information-intelligence transformation. Traditional wisdom emerges here: data
is raw and mirrors the operations and daily transactions of a company; information is the data that
has passed through filtering and aggregation processes and acquired a certain level of contextual
meaning; intelligence elevates the information to the highest level as the result of a complete
understanding of actions contexts and choices.
!oth approaches " technical and managerial " rely on an o#$ective and positive view that
“strategic decisions #ased on accurate and usa#le information lead to an intelligent company”. %ll the
su#$ectivism inherent in social interactions is evacuated and cultural and political issues are not
evo&ed. 'hether the reviewed studies are managerial or technological they share a common idea:
the core of !( )process or tool* is information gathering, analysis and use and
the goal is to support the strategic decision-making process.
The Characteristics of a Business Intelligence Solution
(ingle point of access to information
'ith !( systems organizations can unloc& information held within their data#ases #y giving
authorized users a single point of access to data+a !( portal+in #oth intranet or extranet
environments. 'herever the data resides whether it is stored in operational systems data
warehouses data marts and,or pac&aged applications users can prepare reports and drill deep down
into the information to understand what drives their #usiness without technical &nowledge of the
underlying data structures. The most successful !( applications allow users to do this with an easy-
to-understand non-technical graphical user interface.
/sing !$ in all departments of an organization
There are many different uses for !( systems. !( systems can #e used at every step in the
value chain.
Timely answers to business +uestions
The &ey to unloc&ing information is to give users the tools to quic&ly and easily find answers
to their questions. -ome users will #e satisfied with standard reports that are updated on a regular
#asis li&e current inventory reports sales per channel or customer status reports. .owever the
answers these reports yield can lead to new questions. -ome users will want dynamic access to
information. The information that a user finds in a report will trigger more questions and these
questions will not #e answered in a prepac&aged report.
0aking the most of the internet by creating an extranet
/ou can open up !( system access to users outside the organization through extranet
applications with clearly defined security limits. 0or example customers may want to consult their
ordering history to analyze their #uying patterns and identify cost-saving opportunities. 1r suppliers
may #e interested in gathering sales data.
Selection of BI Tools
-election of a !( tool may turn out to #e a difficult tas&. %t present companies offer a wide
range of products #eginning from simple reporting technologies up to sophisticated !( platforms.
'hile choosing a !( tool it is necessary " li&e in the case of purchasing other (- " to ta&e the
following criteria into consideration: functionality complexity of solutions and compati#ility. (t is
also necessary to remem#er that organization2s informational needs will evolve. Therefore !( tools
should #e up-to-date enough to meet enterprise2s expectations in a few years to come.
%t this stage good mar&et &nowledge of !( is required. Today !( products may #e found in
different segments of the (T mar&et. 3roviders of 453 (( and 653 systems more and more
frequently equip their products with !( modules )e.g. -%3 1racle or 4icrosoft* thus wishing to
ma&e their products more dynamic and analytical. 17%3 techniques and data mining have also #een
914 Challenges of the Knowledge Society. Economy
implemented in database systems (Oracle, Microsoft or IBM)
2
. Planning and budgeting belong to
another segment of the IT maret that uses BI techni!ues. "dditionally, it has to be mentioned that
there is a group of pro#iders that offer BI solutions in a highly speciali$ed area and usually on a #ery
high le#el of customer need satisfaction. %uch products often include best practices for a particular
sector along &ith some future solutions. One cannot forget about open source solutions that are more
and more fre!uently a#ailable on the maret.
In the BI sector ' similarly as in case of other IT sectors ' it is possible to obser#e some
processes of consolidating pro#iders ( purchasing products or e)panding products by means of
functionalities that are offered by the best pro#iders in a gi#en category. *ence, it is necessary to
consider &hether a gi#en enterprise ought to purchase products and technologies from one pro#ider
or if such an enterprise should follo& a principle of selecting the best products in a gi#en category
(e.g. the best tools for O+"P, ,T+, etc.) sold by different pro#iders. In the former case, enterprises
are guaranteed integration of particular products and a similar interface. *o&e#er, it has to be taen
into account that not all solutions are going to be of the highest possible !uality. Pacage purchase of
products fre!uently in#ol#es discounts, &hich is !uite important for enterprises. On the other hand,
purchasing products from se#eral pro#iders may lead to delegating responsibility for particular
module performance to other pro#iders. It is also more difficult to obtain larger discounts &hile
purchasing technologies that come from different pro#iders. There is also some other possibility '
purchase of a ready to use solution instead of a particular technology. In this situation, it is necessary
to learn more about capacities of a gi#en application and then consider &hether such an application
meets enterprise-s needs and &hether there are some elements that the application in !uestion should
be subse!uently pro#ided &ith. Pro#iding an enterprise &ith BI products of an open source type is
another possibility. ,)amples of complimentary or open source products may be pro#ided by %ygate
"nalyst (a tool used for data #isuali$ation), "gata .eports (a reporting tool), Oracle "pplication
,)press (en#ironment for building &eb applications), and cocpit for the management in open source
,.P /ompiere, Business Intelligence .eporting Tool for ,clipse or Mondrian O+"P %er#er. %ome
pro#iders of BI products use free databases. 0or instance, Business Ob1ects uses a complimentary
database called My%2+. 0igure 3
4
represents the largest BI #endors of the &orld IT maret.
2
&&&.intelligententerprise.com.
4
&&&.information&ee.com.
915
Figure 1. BI vendors
Source, www.intelligententerprise.com
The typical BI ‘stack’ or architecture can e represented as having a series o! layers. The ase
is usually shown as source data systems !rom where data is e"tracted, translated and loaded y
e"tract, trans!orm and load #$T%& so!tware into a data warehouse. 'ove this is an application layer
#or BI layer& and on top o! this the presentation or delivery layer which can include e"ecutive
dashoards, scorecards and other tools that make it easier !or managers to !ind and understand the
in!ormation and proactively use it in decision making.
's BI has evolved, the greatest challenge has een how to integrate data on di!!erent systems
accumulated !rom di!!erent vendors over many years. Traditionally, data !lows !rom source systems
to data warehouses then to data marts and cues to e used in BI applications. Source data can now
also come !rom customer !acing applications, suppliers and sources o! e"ternal in!ormation. The data
warehouse has the potential to ecome the in!ormation hu that distriutes data to and !rom many
data sources and applications. So!tware houses used to speciali(e in di!!erent layers o! this BI stack
and usinesses applied a ‘est o! reed’ approach to assemling their own stacks. For e"ample, a
S') $*) system might !eed data to an +racle data warehouse and the !inance !unction might use an
application !rom ,yperion !or consolidation and reports and another !rom S'S !or more advanced
analytics. These solutions were developed y independent so!tware houses to meet di!!erent
usinesses’ needs.
916 Challenges of the Knowledge Society. Economy
This integration challenge is being addressed
4
.
Service-oriented architecture is promoted as a flexible solution which eliminates the need
to develop point-to-point connections between resources. It provides access to data in legacy systems
through ‘services’ which lin together and are combined to provide a business intelligence solution.
The ma!or "#$% "T&% data warehouse and customer relationship management '(#)*
vendors now offer what are claimed to be integrated +I applications% for example S,$ +-%
Informatica $ower(enter% .racle ,pplications and Siebel ,nalytics. ,nd +I vendors began to add
"T& tools% such as +usiness .b!ects /ata Integrator and (ognos /ecisionStream.
The ma!or vendors% S,$% .racle% I+) and )icrosoft% who already had some +I solutions%
have expanded into performance management by ac0uisition. There has been a feeding fren1y and
the big players are still digesting their prey. If they succeed in doing so% they are expected to offer
better integrated +I solutions.
)eanwhile% data integration tools% such as those offered by Informatica% already allow
data from diverse sources to be integrated into the database layer. This enhances the performance and
scalability of +I applications accessing this data.
The Benefits of Business Intelligence
+ecause of the wide applicability of +I in enterprise and extranet deployments% the business
benefits are numerous. These benefits can be grouped into three main categories2 lowering costs%
increasing revenue% and improving customer satisfaction
3
.
Lowering Costs
$mprove operational efficiency
+y giving internal or external customers access to real-time data over the web% customers
can trac their own accounts and answer their own 0uestions. ,s a result% customer satisfaction is
improved while reducing support costs. , significant% added benefit to real time data access is that
data becomes much cleaner. +y reviewing the data themselves% customers can spot errors% and help
improve the 0uality of the information in the data warehouse.
Eliminate report backlog and delays
+usiness intelligence allows business users to design their own 0ueries and reports%
allowing organi1ations to redeploy the programmers who formerly performed this tas. This can
generate significant cost savings in human resources% since sought-after staff can be reallocated to
pro!ects that add more value to the organi1ation.
Negotiate better contracts with suppliers and customers
, solid grasp of facts and figures is invaluable when it comes to negotiating contracts with
suppliers and customers. 4or instance% by analy1ing supplier performance on-time delivery trends%
percentage of re!ects% and price changes will be in an excellent position to discuss all aspects of the
contract as well as possibly negotiate volume discounts. ,nd identifying a customer5s spending
patterns could 0ualify him or her for a particular pacaged deal.
1ind root causes and take action
If one division is doing better or worse than others% identify the root cause and either
implement a best practice or fix the problem. -ith +I% can be found root causes both to problems and
to best practices by simply asing 6-hy78 The process is initiated by analy1ing a global report% say
of sales per 0uarter. "very answer is followed by a new 0uestion% and users can drill deep down into
a report to get to fundamental causes. .nce they have a clear understanding of root causes% they can
tae highly effective action.
4
(I),% Improving decision maing in organi1ations% September 9::;.
3
)ar #itacco and ,strid (arver% The business value of business intelligence% +usiness ob!ect% 9::;.
917
$dentify wasted resources and reduce inventory costs
BI can be apply activity-based costing methods to identify hidden costs or missed
opportunities. From these findings, resources can be allocated to highly profitable products,
customers, and projects, thereby increasing the bottom line. Also, having a clearer understanding of
success of promotions can help to effectively monitor inventory levels.
Increasing Revenue
(ell information to customers, partners and suppliers
Leading organizations are using BI to differentiate their product and service offerings
from competitors through value added, eb-based services. In the past, many departments generated
zero revenue, but no ith BI e!tranets, they create a recurring revenue stream by selling
information to customers, partners, and suppliers.
$mprove strategies with better marketing analysis
"ith easy access to ordering, accounting, production, shipping, customer service, and
even e!ternal databases, mar#eters can find ansers to the most detailed of $uestions such as, %"hat
as the success rate of my direct mail campaign&' or %"hat as the incremental revenue generated
from the ne () ads e just ran&' . "ith this information, the mar#eter can precisely tailor product
launches and promotion campaigns to the targeted audience. *sing BI, companies can micro segment
their mar#ets and gain an edge over the competition.
Empower sales force
Better results from sales force can be achieved by analyzing its selling patterns+ compare
results to targets, to figures from previous years, to other sales staff results, and suggest
improvements. ,ncourage the sales force to focus on high profitability customers and products. (he
sales force can also use BI to analyze data on brands, clients, and distributors.
Improving Customer Satisfaction
2ive users the means to make better decision
"ith access to information, users can ma#e better decisions faster, ithout having to
escalate standard problems up the management hierarchy. (his guarantees pragmatic and effective
solutions since the people directly involved in the operations ma#e decisions. In addition, users have
the increased satisfaction of controlling their on process.
.rovide +uick answers to user +uestions
-ne of the primary benefits of BI is that you can dramatically reduce the time it ta#es for
internal and e!ternal users to get ansers to their $uestions. "ith feer delays and faster response
time, users are empoered to act $uic#ly, based on the information they receive.
)hallenge assumptions with factual information
Almost all businesses rely on assumptions and rule of thumb. .oever, it is orthhile to
challenge these hunches through detailed analysis of operational data, because assumptions and rule
of thumb are fre$uently incorrect.
Conclusions
(he term Business Intelligence may turn out to be a fad. .oever, the underlying concepts,
using information technology to deliver actionable information for decision ma#ers, are essential for
managing today/s global businesses. BI uses both structured and semi-structured data. (he former is
much easier to search but the latter contains the information needed for analysis and decision
ma#ing.
For structured data, many BI tools e!ist for ac$uisition, integration, cleanup, search, analysis,
and delivery. Further or# is needed, hoever, to integrate these tools and to provide actionable
information. BI tools for semi-structured data, on the other hand, are not yet mature.
918 Challenges of the Knowledge Society. Economy
(he development of analytical tools to integrate structured and semi-structured data can
benefit from attention by researchers. (he BI mar#et is groing, and the proportion of semi-
structured data used in daily decisions is groing. ,!ploring the underlying issues and the
development of information technology that provide intelligence to business therefore is a fertile area
for research.
Business intelligence could inform better decision ma#ing in business. ,veryone in
management needs to be alert to this opportunity and the threat that early adapters may achieve a
competitive advantage. But BI is only a technology enabler. 0anagement accountants have
important roles to play if BI is to be of value. (he necessary changes ill have to be implemented
properly. 1eople ill have to use it to produce information and that information still has to be applied
in decision ma#ing and, for those decisions to be effective, they ill have to be managed through to
impact.
(he nature of the management information and analysis re$uired by business has e!panded.
(he range of data to be considered no includes non-financial and e!ternal information. (he
emphasis has shifted from reporting through monitoring to providing information and analysis as
appropriate to users/ roles. (hese users may be strategic managers, #noledge or#ers, people in
operational and customer facing roles or e!ternal sta#eholders and regulators Business intelligence is
evolving to meet these information needs. It no encompasses the reporting and analysis tools used
for performance management by accountants. Advances in data management and better integration
of systems ill enable BI to provide better management information to inform decision ma#ing.
References
Altosoft corporation, Bringing business intelligence to business operations, 0arch 2334
5I0A, Improving decision ma#ing in organizations, 6eptember 2337
0ar# 8itacco and Astrid 5arver, (he business value of business intelligence, Business object, 2337
.intelligententerprise.com
.informationee#.com
.springerlin#.com
businessintelligencetools.org
.ibm.com
.computeree#ly.com
doc_548549418.pdf
Every business is dynamic in nature and is affected by various external and internal factors. These factors include external market conditions, competitors, internal restructuring and re-alignment, operational optimization and paradigm shifts in the business itself.
BUSINESS INTELLIGENCE TOOLS FOR DATA ANALYSIS
AND DECISION MAKING
DEJAN ZDRAVESKI
*
IGOR ZDRAVKOSKI
**
Abstract
Every business is dynamic in nature and is affected by various external and internal factors. These factors
include external market conditions, competitors, internal restructuring and re-alignment, operational
optimization and paradigm shifts in the business itself. New regulations and restrictions, in combination with the
above factors, contribute to the constant evolutionary nature of compelling, business-critical information the
kind of information that an organization needs to sustain and thrive.
!usiness intelligence "#!$%& is broad term that encapsulates the process of gathering information pertaining to
a business and the market it functions in. This information when collated and analyzed in the right manner, can
provide vital insights into the business and can be a tool to improve efficiency, reduce costs, reduce time lags
and bring many positive changes. ' business intelligence application helps to achieve precisely that.
(uccessful organizations maximize the use of their data assets through business intelligence technology. The first
data warehousing and decision support tools introduced companies to the power and benefits of accessing and
analyzing their corporate data. !usiness users at every level found new, more sophisticated ways to analyze and
report on the information mined from their vast data warehouses.
)hoosing a !usiness $ntelligence offering is an important decision for an enterprise, one that will have a
significant impact throughout the enterprise. The choice of a !$ offering will affect people up and down the
chain of command "senior management, analysts, and line managers& and across functional areas "sales,
finance, and operations&. $t will affect business users, application developers, and $T professionals.
!$ applications include the activities of decision support systems "*((&, +uery and reporting, online analytical
processing ",-'.&, statistical analysis, forecasting, and data mining. 'nother way of phrasing this is that !$
applications take data that is generated by the operations of an enterprise and translate that data into relevant
and useful information for consumption by people throughout the enterprise.
Keywords: !usiness intelligence, application, decision making, knowledge, data mining, data warehouse
Intro!ct"on
The final decades of the 20th century and the beginning of the 21st have been marked by a
staggering proliferation of information and communication technologies throughout the
industrialized world. Not only do globalization trends bring a turbulent and most often unequal
competitive environment they also propagate waves of !managerial imperatives" # such as total
quality$ reengineering and integrated systems # that e%ert tremendous pressure on organizations
wanting not only to survive but to succeed. &n addition to performance and effectiveness global
organizations are asked to display ethical social and environmental responsibility. This entire conte%t
makes the task of managing information a formidable challenge.
't present information management is seen as one of the biggest challenges characterizing
today(s corporate conte%t. ' combination of constant technological innovation and increasing
competitiveness makes the management of information a difficult task one which requires decision)
making processes that are built on reliable and timely information gathered from internal and
e%ternal sources. 'lthough the volume of information available is increasing this does not
automatically mean that people are able to derive value from it. &n the &T field after years of
significant investments to create technological platforms that support all business processes
**
+h, -aculty of .conomics)+rilep)/acedonia 0e)mail1 zigor2002yahoo.com3.
912 Challenges of the Knowledge Society. Economy
(processes that are “reengineered” and “integrated”) and that strengthen the efficiency of the
operational structure (after undergoing “quality” programs), organizations are supposed to have
reached a point where the implementation of IT solutions for strategic decision-maing processes
!ecomes possi!le and necessary" This conte#t e#plains the emergence of the area generally nown as
“!usiness intelligence” ($I), seen as an answer to current needs in terms of information for strategic
decision-maing through intensive use of information technology (IT)"
Definition of Business intelligence
The literature review of $I reveals few studies" %ost of the articles are conceptual" &hat's
more, throughout the literature, meets the traditional “separation” !etween technical and managerial
aspects, outlining two !road patterns
(
" The technological approach, which prevails in most studies,
presents $I as a set of tools that support the storage and analysis of information" This encompasses a
!road category of applications and technologies for gathering, storing, analyzing, and providing
access to data to help enterprise users mae !etter !usiness decisions" Those $I tools include decision
support systems, query and reporting, online analytical processing ()*+,), statistical analysis,
forecasting and data mining" The focus is not on the process itself, !ut on the technologies that allow
the recording, recovery, manipulation and analysis of information" -ophisticated use of warehoused
data occurs when advanced data mining techniques are applied to change data into information" .ata
mining is the utilization of mathematical and statistical applications that process and analyze data"
%athematics refers to equations or algorithms that process data to discover patterns and relationships
among varia!les" -tatistics generally shed light on the ro!ustness and validity of the relationships that
e#ist in the data mining model" *eading methods of data mining include regression, segmentation
classification, neural networs, clustering and affinity analysis" The synergy created !etween data
warehousing and data mining allows nowledge seeers to leverage their massive data assets, thus
improving the quality and effectiveness of their decisions" The growing requirements for data mining
and real time analysis of information will !e a driving force in the development of new data
warehouse architectures and methods and, conversely, the development of new data mining methods
and applications"
In short, $I is a wide set of tools and applications for gathering, consolidation, analysis and
dissemination aiming at to improve the power to decision process" The components of !usiness
intelligence that focus in collect and consolidation can involve data management software's to access
data varia!les, e#tract, transform and load tools that also enhance data access and storage in a data
warehouse or data mart" In the steps of analysis and distri!ution, each time more different products
are launched and integrated with o!/ective to tae care of the different use of the information" These
products can include the creation of reports, the fine-tuned dash!oards containing customized
performance indicators visually rich presentations using gauges, maps, charts, and other graphical
elements to show multiple results together, the generation of )*+, cu!es and the data mining
software's to discover information hidden within valua!le data assets, using advanced mathematical
and statistical techniques, can uncover veins of surprising, golden insights in a mountain of factual
data" 0igure ( presents a proposal of $I architecture, distri!uting the different technologies and
applications argued in function of its main contri!ution in each one of the steps in the $I process"
The managerial approach sees $I as a process in which data from inside and outside the
company are integrated in order to generate information relevant to the decision-maing process" The
role of $I here is related to the whole informational environment and !y which operational data
gathered from transactional systems and e#ternal sources can !e analyzed to reveal the “strategic”
!usiness dimensions" 0rom this perspective emerge concepts such as the “intelligent company”1 one
that uses $I to mae faster and smarter decisions than its competitors" ,ut simply, “intelligence”
entails the reduction of a huge volume of data into nowledge through a process of filtering,
(
+ltosoft corporation, $ringing !usiness intelligence to !usiness operations, %arch 2334"
913
analyzing and reporting information. The explanation of how companies acquire “intelligence”
would lie in the data-information-intelligence transformation. Traditional wisdom emerges here: data
is raw and mirrors the operations and daily transactions of a company; information is the data that
has passed through filtering and aggregation processes and acquired a certain level of contextual
meaning; intelligence elevates the information to the highest level as the result of a complete
understanding of actions contexts and choices.
!oth approaches " technical and managerial " rely on an o#$ective and positive view that
“strategic decisions #ased on accurate and usa#le information lead to an intelligent company”. %ll the
su#$ectivism inherent in social interactions is evacuated and cultural and political issues are not
evo&ed. 'hether the reviewed studies are managerial or technological they share a common idea:
the core of !( )process or tool* is information gathering, analysis and use and
the goal is to support the strategic decision-making process.
The Characteristics of a Business Intelligence Solution
(ingle point of access to information
'ith !( systems organizations can unloc& information held within their data#ases #y giving
authorized users a single point of access to data+a !( portal+in #oth intranet or extranet
environments. 'herever the data resides whether it is stored in operational systems data
warehouses data marts and,or pac&aged applications users can prepare reports and drill deep down
into the information to understand what drives their #usiness without technical &nowledge of the
underlying data structures. The most successful !( applications allow users to do this with an easy-
to-understand non-technical graphical user interface.
/sing !$ in all departments of an organization
There are many different uses for !( systems. !( systems can #e used at every step in the
value chain.
Timely answers to business +uestions
The &ey to unloc&ing information is to give users the tools to quic&ly and easily find answers
to their questions. -ome users will #e satisfied with standard reports that are updated on a regular
#asis li&e current inventory reports sales per channel or customer status reports. .owever the
answers these reports yield can lead to new questions. -ome users will want dynamic access to
information. The information that a user finds in a report will trigger more questions and these
questions will not #e answered in a prepac&aged report.
0aking the most of the internet by creating an extranet
/ou can open up !( system access to users outside the organization through extranet
applications with clearly defined security limits. 0or example customers may want to consult their
ordering history to analyze their #uying patterns and identify cost-saving opportunities. 1r suppliers
may #e interested in gathering sales data.
Selection of BI Tools
-election of a !( tool may turn out to #e a difficult tas&. %t present companies offer a wide
range of products #eginning from simple reporting technologies up to sophisticated !( platforms.
'hile choosing a !( tool it is necessary " li&e in the case of purchasing other (- " to ta&e the
following criteria into consideration: functionality complexity of solutions and compati#ility. (t is
also necessary to remem#er that organization2s informational needs will evolve. Therefore !( tools
should #e up-to-date enough to meet enterprise2s expectations in a few years to come.
%t this stage good mar&et &nowledge of !( is required. Today !( products may #e found in
different segments of the (T mar&et. 3roviders of 453 (( and 653 systems more and more
frequently equip their products with !( modules )e.g. -%3 1racle or 4icrosoft* thus wishing to
ma&e their products more dynamic and analytical. 17%3 techniques and data mining have also #een
914 Challenges of the Knowledge Society. Economy
implemented in database systems (Oracle, Microsoft or IBM)
2
. Planning and budgeting belong to
another segment of the IT maret that uses BI techni!ues. "dditionally, it has to be mentioned that
there is a group of pro#iders that offer BI solutions in a highly speciali$ed area and usually on a #ery
high le#el of customer need satisfaction. %uch products often include best practices for a particular
sector along &ith some future solutions. One cannot forget about open source solutions that are more
and more fre!uently a#ailable on the maret.
In the BI sector ' similarly as in case of other IT sectors ' it is possible to obser#e some
processes of consolidating pro#iders ( purchasing products or e)panding products by means of
functionalities that are offered by the best pro#iders in a gi#en category. *ence, it is necessary to
consider &hether a gi#en enterprise ought to purchase products and technologies from one pro#ider
or if such an enterprise should follo& a principle of selecting the best products in a gi#en category
(e.g. the best tools for O+"P, ,T+, etc.) sold by different pro#iders. In the former case, enterprises
are guaranteed integration of particular products and a similar interface. *o&e#er, it has to be taen
into account that not all solutions are going to be of the highest possible !uality. Pacage purchase of
products fre!uently in#ol#es discounts, &hich is !uite important for enterprises. On the other hand,
purchasing products from se#eral pro#iders may lead to delegating responsibility for particular
module performance to other pro#iders. It is also more difficult to obtain larger discounts &hile
purchasing technologies that come from different pro#iders. There is also some other possibility '
purchase of a ready to use solution instead of a particular technology. In this situation, it is necessary
to learn more about capacities of a gi#en application and then consider &hether such an application
meets enterprise-s needs and &hether there are some elements that the application in !uestion should
be subse!uently pro#ided &ith. Pro#iding an enterprise &ith BI products of an open source type is
another possibility. ,)amples of complimentary or open source products may be pro#ided by %ygate
"nalyst (a tool used for data #isuali$ation), "gata .eports (a reporting tool), Oracle "pplication
,)press (en#ironment for building &eb applications), and cocpit for the management in open source
,.P /ompiere, Business Intelligence .eporting Tool for ,clipse or Mondrian O+"P %er#er. %ome
pro#iders of BI products use free databases. 0or instance, Business Ob1ects uses a complimentary
database called My%2+. 0igure 3
4
represents the largest BI #endors of the &orld IT maret.
2
&&&.intelligententerprise.com.
4
&&&.information&ee.com.
915
Figure 1. BI vendors
Source, www.intelligententerprise.com
The typical BI ‘stack’ or architecture can e represented as having a series o! layers. The ase
is usually shown as source data systems !rom where data is e"tracted, translated and loaded y
e"tract, trans!orm and load #$T%& so!tware into a data warehouse. 'ove this is an application layer
#or BI layer& and on top o! this the presentation or delivery layer which can include e"ecutive
dashoards, scorecards and other tools that make it easier !or managers to !ind and understand the
in!ormation and proactively use it in decision making.
's BI has evolved, the greatest challenge has een how to integrate data on di!!erent systems
accumulated !rom di!!erent vendors over many years. Traditionally, data !lows !rom source systems
to data warehouses then to data marts and cues to e used in BI applications. Source data can now
also come !rom customer !acing applications, suppliers and sources o! e"ternal in!ormation. The data
warehouse has the potential to ecome the in!ormation hu that distriutes data to and !rom many
data sources and applications. So!tware houses used to speciali(e in di!!erent layers o! this BI stack
and usinesses applied a ‘est o! reed’ approach to assemling their own stacks. For e"ample, a
S') $*) system might !eed data to an +racle data warehouse and the !inance !unction might use an
application !rom ,yperion !or consolidation and reports and another !rom S'S !or more advanced
analytics. These solutions were developed y independent so!tware houses to meet di!!erent
usinesses’ needs.
916 Challenges of the Knowledge Society. Economy
This integration challenge is being addressed
4
.
Service-oriented architecture is promoted as a flexible solution which eliminates the need
to develop point-to-point connections between resources. It provides access to data in legacy systems
through ‘services’ which lin together and are combined to provide a business intelligence solution.
The ma!or "#$% "T&% data warehouse and customer relationship management '(#)*
vendors now offer what are claimed to be integrated +I applications% for example S,$ +-%
Informatica $ower(enter% .racle ,pplications and Siebel ,nalytics. ,nd +I vendors began to add
"T& tools% such as +usiness .b!ects /ata Integrator and (ognos /ecisionStream.
The ma!or vendors% S,$% .racle% I+) and )icrosoft% who already had some +I solutions%
have expanded into performance management by ac0uisition. There has been a feeding fren1y and
the big players are still digesting their prey. If they succeed in doing so% they are expected to offer
better integrated +I solutions.
)eanwhile% data integration tools% such as those offered by Informatica% already allow
data from diverse sources to be integrated into the database layer. This enhances the performance and
scalability of +I applications accessing this data.
The Benefits of Business Intelligence
+ecause of the wide applicability of +I in enterprise and extranet deployments% the business
benefits are numerous. These benefits can be grouped into three main categories2 lowering costs%
increasing revenue% and improving customer satisfaction
3
.
Lowering Costs
$mprove operational efficiency
+y giving internal or external customers access to real-time data over the web% customers
can trac their own accounts and answer their own 0uestions. ,s a result% customer satisfaction is
improved while reducing support costs. , significant% added benefit to real time data access is that
data becomes much cleaner. +y reviewing the data themselves% customers can spot errors% and help
improve the 0uality of the information in the data warehouse.
Eliminate report backlog and delays
+usiness intelligence allows business users to design their own 0ueries and reports%
allowing organi1ations to redeploy the programmers who formerly performed this tas. This can
generate significant cost savings in human resources% since sought-after staff can be reallocated to
pro!ects that add more value to the organi1ation.
Negotiate better contracts with suppliers and customers
, solid grasp of facts and figures is invaluable when it comes to negotiating contracts with
suppliers and customers. 4or instance% by analy1ing supplier performance on-time delivery trends%
percentage of re!ects% and price changes will be in an excellent position to discuss all aspects of the
contract as well as possibly negotiate volume discounts. ,nd identifying a customer5s spending
patterns could 0ualify him or her for a particular pacaged deal.
1ind root causes and take action
If one division is doing better or worse than others% identify the root cause and either
implement a best practice or fix the problem. -ith +I% can be found root causes both to problems and
to best practices by simply asing 6-hy78 The process is initiated by analy1ing a global report% say
of sales per 0uarter. "very answer is followed by a new 0uestion% and users can drill deep down into
a report to get to fundamental causes. .nce they have a clear understanding of root causes% they can
tae highly effective action.
4
(I),% Improving decision maing in organi1ations% September 9::;.
3
)ar #itacco and ,strid (arver% The business value of business intelligence% +usiness ob!ect% 9::;.
917
$dentify wasted resources and reduce inventory costs
BI can be apply activity-based costing methods to identify hidden costs or missed
opportunities. From these findings, resources can be allocated to highly profitable products,
customers, and projects, thereby increasing the bottom line. Also, having a clearer understanding of
success of promotions can help to effectively monitor inventory levels.
Increasing Revenue
(ell information to customers, partners and suppliers
Leading organizations are using BI to differentiate their product and service offerings
from competitors through value added, eb-based services. In the past, many departments generated
zero revenue, but no ith BI e!tranets, they create a recurring revenue stream by selling
information to customers, partners, and suppliers.
$mprove strategies with better marketing analysis
"ith easy access to ordering, accounting, production, shipping, customer service, and
even e!ternal databases, mar#eters can find ansers to the most detailed of $uestions such as, %"hat
as the success rate of my direct mail campaign&' or %"hat as the incremental revenue generated
from the ne () ads e just ran&' . "ith this information, the mar#eter can precisely tailor product
launches and promotion campaigns to the targeted audience. *sing BI, companies can micro segment
their mar#ets and gain an edge over the competition.
Empower sales force
Better results from sales force can be achieved by analyzing its selling patterns+ compare
results to targets, to figures from previous years, to other sales staff results, and suggest
improvements. ,ncourage the sales force to focus on high profitability customers and products. (he
sales force can also use BI to analyze data on brands, clients, and distributors.
Improving Customer Satisfaction
2ive users the means to make better decision
"ith access to information, users can ma#e better decisions faster, ithout having to
escalate standard problems up the management hierarchy. (his guarantees pragmatic and effective
solutions since the people directly involved in the operations ma#e decisions. In addition, users have
the increased satisfaction of controlling their on process.
.rovide +uick answers to user +uestions
-ne of the primary benefits of BI is that you can dramatically reduce the time it ta#es for
internal and e!ternal users to get ansers to their $uestions. "ith feer delays and faster response
time, users are empoered to act $uic#ly, based on the information they receive.
)hallenge assumptions with factual information
Almost all businesses rely on assumptions and rule of thumb. .oever, it is orthhile to
challenge these hunches through detailed analysis of operational data, because assumptions and rule
of thumb are fre$uently incorrect.
Conclusions
(he term Business Intelligence may turn out to be a fad. .oever, the underlying concepts,
using information technology to deliver actionable information for decision ma#ers, are essential for
managing today/s global businesses. BI uses both structured and semi-structured data. (he former is
much easier to search but the latter contains the information needed for analysis and decision
ma#ing.
For structured data, many BI tools e!ist for ac$uisition, integration, cleanup, search, analysis,
and delivery. Further or# is needed, hoever, to integrate these tools and to provide actionable
information. BI tools for semi-structured data, on the other hand, are not yet mature.
918 Challenges of the Knowledge Society. Economy
(he development of analytical tools to integrate structured and semi-structured data can
benefit from attention by researchers. (he BI mar#et is groing, and the proportion of semi-
structured data used in daily decisions is groing. ,!ploring the underlying issues and the
development of information technology that provide intelligence to business therefore is a fertile area
for research.
Business intelligence could inform better decision ma#ing in business. ,veryone in
management needs to be alert to this opportunity and the threat that early adapters may achieve a
competitive advantage. But BI is only a technology enabler. 0anagement accountants have
important roles to play if BI is to be of value. (he necessary changes ill have to be implemented
properly. 1eople ill have to use it to produce information and that information still has to be applied
in decision ma#ing and, for those decisions to be effective, they ill have to be managed through to
impact.
(he nature of the management information and analysis re$uired by business has e!panded.
(he range of data to be considered no includes non-financial and e!ternal information. (he
emphasis has shifted from reporting through monitoring to providing information and analysis as
appropriate to users/ roles. (hese users may be strategic managers, #noledge or#ers, people in
operational and customer facing roles or e!ternal sta#eholders and regulators Business intelligence is
evolving to meet these information needs. It no encompasses the reporting and analysis tools used
for performance management by accountants. Advances in data management and better integration
of systems ill enable BI to provide better management information to inform decision ma#ing.
References
Altosoft corporation, Bringing business intelligence to business operations, 0arch 2334
5I0A, Improving decision ma#ing in organizations, 6eptember 2337
0ar# 8itacco and Astrid 5arver, (he business value of business intelligence, Business object, 2337
.intelligententerprise.com
.informationee#.com
.springerlin#.com
businessintelligencetools.org
.ibm.com
.computeree#ly.com
doc_548549418.pdf