9 vol9no1

Journal of Theoretical and Applied Information Technology

© 2005 - 2009 JATIT. All rights reserved.

www.jatit.org

BUSINESS INTELLIGENCE: CONCEPTS, COMPONENTS,
TECHNIQUES AND BENEFITS
JAYANTHI RANJAN
Institute of Management Technology,
Ghaziabad, Uttar Pradesh, India
Email: jranjan@imt.edu

ABSTRACT

For companies maintaining direct contact with large numbers of customers, however, a growing number
channel-oriented applications (e.g. e-commerce support, call center support) create a new data
management challenge: that is effective way of integrating enterprise applications in real time. To learn
from the past and forecast the future, many companies are adopting Business Intelligence (BI) tools and
systems. Companies have understood the importance of enforcing achievements of the goals defined by
their business strategies through business intelligence concepts. It describes the insights on the role and
requirement of real time BI by examining the business needs. The paper explores the concepts of BI, its
components, emergence of BI, benefits of BI, factors influencing BI, technology requirements, designing
and implementing business intelligence, and various BI techniques.

1. INTRODUCTION A specialized field of business intelligence
known as competitive intelligence focuses solely
Business intelligence (BI) has two basic different on the external competitive environment.
meanings related to the use of the term Information is gathered on the actions of
intelligence. The primary, less frequently, is the competitors and decisions are made based on this
human intelligence capacity applied in business information. Little if any attention is paid to
affairs/activities. Intelligence of Business is a gathering internal information.
new field of the investigation of the application
of human cognitive faculties and artificial In modern businesses, increasing standards,
intelligence technologies to the management and automation, and technologies have led to vast
decision support in different business problems. amounts of data becoming available. Data
warehouse technologies have set up repositories
The second relates to the intelligence as to store this data. Improved Extract, transform,
information valued for its currency and relevance. load (ETL) and even recently Enterprise
It is expert information, knowledge and Application Integration tools have increased the
technologies efficient in the management of speedy collecting of data. OLAP reporting
organizational and individual business. Therefore, technologies have allowed faster generation of
in this sense, business intelligence is a broad new reports which analyze the data. Business
category of applications and technologies for intelligence has now become the art of sifting
gathering, providing access to, and analyzing through large amounts of data, extracting
data for the purpose of helping enterprise users pertinent information, and turning that
make better business decisions. The term implies information into knowledge upon which actions
having a comprehensive knowledge of all of the can be taken.
factors that affect the business. It is imperative
that firms have an in depth knowledge about The paper explores the concepts of BI, its
factors such as the customers, competitors, components, emergence of BI, benefits of BI,
business partners, economic environment, and factors influencing BI, technology requirements,
internal operations to make effective and good designing and implementing business
quality business decisions. Business intelligence intelligence, cultural imperatives, and various BI
enables firms to make these kinds of decisions. techniques. The paper would be useful for

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budding researchers in the field of BI to integrated solution for companies, within which
understand the basic concepts. the business requirement is definitely the key
factor that drives technology innovation. How to
2. BUSINESS INTELLIGENCE identify and creatively address key business
issues is therefore always the major challenge of
Stackowiak et al. (2007) define Business a BI application to achieve real business impact.
intelligence as the process of taking large
amounts of data, analyzing that data, and (Golfarelli et.al, 2004) defined BI that includes
presenting a high-level set of reports that effective data warehouse and also a reactive
condense the essence of that data into the basis component capable of monitoring the time-
of business actions, enabling management to critical operational processes to allow tactical
make fundamental daily business decisions. (Cui and operational decision-makers to tune their
et al, 2007) view BI as way and method of actions according to the company strategy.
improving business performance by providing (Gangadharan and Swamy, 2004) define BI as
powerful assists for executive decision maker to the result of in-depth analysis of detailed
enable them to have actionable information at business data, including database and application
hand. BI tools are seen as technology that technologies, as well as analysis practices.
enables the efficiency of business operation by (Gangadharan and Swamy, 2004) widen the
providing an increased value to the enterprise definition of BI as technically much broader
information and hence the way this information tools, that includes potentially encompassing
is utilized. knowledge management, enterprise resource
planning, decision support systems and data
Zeng et al. (2006) define BI as “The process of mining.
collection, treatment and diffusion of
information that has an objective, the reduction BI includes several software for Extraction,
of uncertainty in the making of all strategic Transformation and Loading (ETL), data
decisions.” Experts describe Business warehousing, database query and reporting,
intelligence as a “business management term (Berson et.al, 2002; Curt Hall, 1999)
used to describe applications and technologies multidimensional/on-line analytical processing
which are used to gather, provide access to (OLAP) data analysis, data mining and
analyze data and information about an enterprise, visualization.
in order to help them make better informed
business decisions.” 3. COMPONENTS OF BI.

(Tvrdíková, 2007) describes the basic OLAP (On-line analytical processing): It
characteristic for BI tool is that it is ability to refers to the way in which business users can
collect data from heterogeneous source, to slice and dice their way through data using
possess advance analytical methods, and the sophisticated tools that allow for the navigation
ability to support multi users demands. of dimensions such as time or hierarchies. Online
Analytical Processing or OLAP provides
Zeng et al. (2006) categorized BI technology multidimensional, summarized views of business
based on the method of information delivery; data and is used for reporting, analysis, modeling
reporting, statistical analysis, ad-hoc analysis and planning for optimizing the business. OLAP
and predicative analysis. techniques and tools can be used to work with
data warehouses or data marts designed for
The concept of Business Intelligence (BI) is sophisticated enterprise intelligence systems.
brought up by Gartner Group since 1996. It is These systems process queries required to
defined as the application of a set of discover trends and analyze critical factors.
methodologies and technologies, such as J2EE, Reporting software generates aggregated views
DOTNET, Web Services, XML, data warehouse, of data to keep the management informed about
OLAP, Data Mining, representation technologies, the state of their business. Other BI tools are
etc, to improve enterprise operation effectiveness, used to store and analyze data, such as data
support management/decision to achieve mining and data warehouses; decision support
competitive advantages. Business Intelligence by systems and forecasting; document warehouses
today is never a new technology instead of an and document management; knowledge
management; mapping, information visualization,

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and dash boarding; management information data mart should look like and each department's
systems, geographic information systems; Trend data mart is peculiar to and specific to its own
Analysis; Software as a Service (SaaS). needs. Similar to data warehouses, data marts
contain operational data that helps business
Advanced Analytics: it is referred to as data experts to strategize based on analyses of past
mining, forecasting or predictive analytics, this trends and experiences. The key difference is
takes advantage of statistical analysis techniques that the creation of a data mart is predicated on a
to predict or provide certainty measures on facts. specific, predefined need for a certain grouping
and configuration of select data. There can be
Corporate Performance Management (Portals, multiple data marts inside an enterprise. A data
Scorecards, Dashboards): this general category mart can support a particular business function,
usually provides a container for several pieces to business process or business unit.
plug into so that the aggregate tells a story. For
example, a balanced scorecard that displays A data mart as described by (Inmon, 1999) is a
portlets for financial metrics combined with say collection of subject areas organized for decision
organizational learning and growth metrics. support based on the needs of a given department.
Finance has their data mart, marketing has theirs,
Real time BI: It allows for the real time and sales have theirs and so on. And the data
distribution of metrics through email, messaging mart for marketing only faintly resembles
systems and/or interactive displays. anyone else's data mart.

Data Warehouse and data marts: The data BI tools are widely accepted as a new
warehouse is the significant component of middleware between transactional applications
business intelligence. It is subject oriented, and decision support applications, thereby
integrated. The data warehouse supports the decoupling systems tailored to an efficient
physical propagation of data by handling the handling of business transactions from systems
numerous enterprise records for integration, tailored to an efficient support of business
cleansing, aggregation and query tasks. It can decisions. The capabilities of BI include decision
also contain the operational data which can be support, online analytical processing, statistical
defined as an updateable set of integrated data analysis, forecasting, and data mining. The
used for enterprise wide tactical decision-making following are the major components that
of a particular subject area. It contains live data, constitute BI.
not snapshots, and retains minimal history. Data
sources can be operational databases, historical Data Sources
data, external data for example, from market
research companies or from the Internet), or Data sources can be operational databases,
information from the already existing data historical data, external data for example, from
warehouse environment. The data sources can be market research companies or from the Internet),
relational databases or any other data structure or information from the already existing data
that supports the line of business applications. warehouse environment. The data sources can be
They also can reside on many different platforms relational databases or any other data structure
and can contain structured information, such as that supports the line of business applications.
tables or spreadsheets, or unstructured They also can reside on many different platforms
information, such as plaintext files or pictures and can contain structured information, such as
and other multimedia information. A data mart tables or spreadsheets, or unstructured
as described by (Inmon, 1999) is a collection of information, such as plaintext files or pictures
subject areas organized for decision support and other multimedia information.
based on the needs of a given department.
Finance has their data mart, marketing has theirs, 4. ISSUES IN BI
and sales have theirs and so on. And the data
mart for marketing only faintly resembles Experts View: Experts view BI in different
anyone else's data mart. Perhaps most ways. Data warehousing experts view BI as
importantly, (Inmon, 1999) the individual supplementary systems and is very new to them.
departments own the hardware, software, data These experts treat BI as technology platform for
and programs that constitute the data mart. Each decision support application. The author is of
department has its own interpretation of what a opinion that to data mining experts BI is set of

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advanced decision support systems with data analysis relating to their business, particularly in
mining techniques and applications of algorithms. frontline operations. They will come to expect up
To statisticians BI is viewed as a forecasting and to date and fresh information in the same fashion
multidimensional analysis based tool. as they monitor stock quotes online. Monthly
and even weekly analysis will not suffice. In the
Approaches in Data Warehousing: The main not too distant future companies will become
key to successful BI system is consolidating data dependent on real time business information in
from the many different enterprise operational much the same fashion as people come to expect
systems into an enterprise data warehouse. Very to get information on the internet in just one or
few organizations have a full-fledged enterprise two clicks.
data warehouse. This is due to the vast scope of
effort towards consolidating the entire enterprise Also in the near future business information will
data. (Berson et.al, 2002) emphasizes that in become more democratized where end users
view of emerging highly dynamic business from throughout the organization will be able to
environment, only the most competitive view information on their particular segment to
enterprises will achieve sustained market success. see how it's performing.
The organizations will distinguish themselves by
the capability to leverage information about their So, in the future, the capability requirements of
market place, customers, and operations to business intelligence will increase in the same
capitalize on the business opportunities.
way that consumer expectations increase. It is
therefore imperative that companies increase at
Analysis of right information: Several surveys the same pace or even faster to stay competitive.
including Gartner, Forrester and International
Data Centre report that most of the firms
throughout the globe are interested in investing 6. REASONS FOR BUSINESS
in BI. It is to be noted that despite major INTELLIGENCE
investments in enterprise resource planning
(ERP) and customer relationship management Business Intelligence enables organizations to
(CRM) over the last decade businesses are make well informed business decisions and thus
struggling to achieve competitive advantage. It is can be the source of competitive advantages.
due to the information captured by these systems. This is especially true when firms are able to
Any corporate would look forward for one goal extrapolate information from indicators in the
called ‘right access to information quickly’. external environment and make accurate
Hence, the firms need to support the analysis and forecasts about future trends or economic
application of information in order to make conditions. Once business intelligence is
operational decisions. Say for marking seasonal gathered effectively and used proactively then
merchandise or providing certain the firms can make decisions that benefit the
recommendations to customers, firms need right firms.
access to information quickly. Implementing
smarter business processes is where business The ultimate objective of business intelligence is
intelligence influences and influences the bottom to improve the timeliness and quality of
line and returns value to any firm. information. Timely and good quality
information is like having a crystal ball that can
5. FUTURE OF BUSINESS give an indication of what's the best course to
INTELLIGENCE take. Business intelligence reveals:

In this rapidly changing world consumers are • The position of the firm as in
now demanding quicker more efficient service comparison to its competitors
from businesses. To stay competitive companies • Changes in customer behavior and
must meet or exceed the expectations of spending patterns
consumers. Companies will have to rely more • The capabilities of the firm
heavily on their business intelligence systems to • Market conditions, future trends,
stay ahead of trends and future events. Business demographic and economic information
intelligence users are beginning to demand Real • The social, regulatory, and political
time Business Intelligence] or near real time environment

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• What the other firms in the market are
doing

Businesses realize that in this very competitive,
fast paced and ever-changing business
environment, a key competitive quantity is how
quickly they respond and adapt to change.
Business intelligence enables them to use
information gathered to quickly and constantly
respond to changes.

The Fig.1 presents an understanding of BI. A BI
system in other words is a combination of data
warehousing and decision support systems. The
figure also reveals how data from disparate
sources can be extracted and stored to be
retrieved for analysis. The basic BI functions and
reports are shown in fig 1. Fig 1. A basic understanding of BI

The primary activities include gathering, 7. BENEFITS OF BI
preparing and analyzing data. The data itself
must be of high quality. The various sources of BI provides many benefits to companies utilizing
data is collected, transformed, cleansed, loaded it. It can eliminate a lot of the guesswork within
and stored in a warehouse. The relevant data is an organization, enhance communication among
for a specific business area that is extracted from departments while coordinating activities, and
the data warehouse. A BI organization fully enable companies to respond quickly to changes
exploits data at every phase of the BI in financial conditions, customer preferences,
architecture as it progresses through various and supply chain operations. BI improves the
levels of informational metamorphosis. The raw overall performance of the company using it.
data is born in operational environments, where
transactional data pours in from every source and
every corner of the enterprise. Therefore, that is Information is often regarded as the second most
the business intelligent organization vision: A important resource a company has (a company's
natural flow of data, from genesis to action. In most valuable assets are its people). So when a
addition, at each step in the flow, the data is fully company can make decisions based on timely
exploited to ensure the increase of information and accurate information, the company can
value for the enterprise. The challenge for BI, of improve its performance. BI also expedites
course, is to build any organization’s vision. decision-making, as acting quickly and correctly
on information before competing businesses do
can often result in competitively superior
performance. It can also improve customer
experience, allowing for the timely and
appropriate response to customer problems and
priorities.

The firms have recognized the importance of
business intelligence for the masses has arrived.
Some of them are listed below.

• With BI superior tools, now employees
can also easily convert their business
knowledge via the analytical
intelligence to solve many business
issues, like increase response rates from

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direct mail, telephone, e-mail, and valuable market share. Business Intelligence tells
Internet delivered marketing campaigns. what actions our competitors are taking, so one
• With BI, firms can identify their most can make better informed decisions.
profitable customers and the underlying
reasons for those customers’ loyalty, as 8. BUSINESS INTELLIGENCE
well as identify future customers with TECHNOLOGY
comparable if not greater potential.
• Analyze click-stream data to improve e- Business intelligence provides organizational
commerce strategies. data in such a way that the organizational
• Quickly detect warranty-reported knowledge filters can easily associate with this
problems to minimize the impact of data and turn it into information for the
product design deficiencies. organization. Persons involved in business
• Discover money-laundering criminal intelligence processes may use application
activities. software and other technologies to gather, store,
• Analyze potential growth customer analyze, and provide access to data, and present
profitability and reduce risk exposure that data in a simple, useful manner. The
through more accurate financial credit software aids in Business performance
scoring of their customers. management, and aims to help people make
• Determine what combinations of "better" business decisions by making accurate,
products and service lines customers are current, and relevant information available to
likely to purchase and when. them when they need it. Some businesses use
• Analyze clinical trials for experimental data warehouses because they are a logical
drugs. collection of information gathered from various
• Set more profitable rates for insurance operational databases for the purpose of creating
premiums. business intelligence.
• Reduce equipment downtime by
applying predictive maintenance. In order for BI system to work effectively there
• Determine with attrition and churn must be some technical constraints in place. BI
analysis why customers leave for technical requirements have to address the
competitors and/or become the following issues:
customers.
• Detect and deter fraudulent behavior, • Security and specified user access to the
such as from usage spikes when credit warehouse
or phone cards are stolen. • Data volume (capacity)
• Identify promising new molecular drug • How long data will be stored (data
compounds. retention)
• Benchmark and performance targets
Customers are the most critical aspect to a
company's success. Without them a company People working in business intelligence have
cannot exist. So it is very important that firms developed tools that ease the work, especially
have information on their preferences. Firms when the intelligence task involves gathering and
must quickly adapt to their changing demands. analyzing large quantities of unstructured data.
Business Intelligence enables firms to gather Each vendor typically defines Business
information on the trends in the marketplace and Intelligence their own way, and markets tools to
come up with innovative products or services in do BI the way that they see it.
anticipation of customer's changing demands.
Business intelligence includes tools in various
Competitors can be a huge hurdle on firm’s way categories, including the following:
to success. Their objectives are the same as
firms’ and that is to maximize profits and
customer satisfaction. In order to be successful • AQL - Associative Query Logic
firms must stay one step ahead of the • Scorecarding
competitors. In business we don't want to play • Business Performance Management and
the catch up game because we would have lost Performance Measurement
• Business Planning

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• Business Process Re-engineering 9. DESIGNING AND IMPLEMENTING A
• Competitive Analysis BUSINESS INTELLIGENCE
• Customer Relationship Management
(CRM) and Marketing When implementing a BI programme one might
• Data mining (DM), Data Farming, and like to pose a number of questions and take a
Data warehouses number of resultant decisions, such as:
• Decision Support Systems (DSS) and
Forecasting • Goal Alignment queries: The first step
• Document warehouses and Document determines the short and medium-term
Management purposes of the programme. What
• Enterprise Management systems strategic goal(s) of the organization will
• Executive Information Systems (EIS) the programme address? What
• Finance and Budgeting organizational mission/vision does it
• Human Resources relate to? A crafted hypothesis needs to
• Knowledge Management detail how this initiative will eventually
• Mapping, Information visualization, and improve results / performance (i.e. a
Dash boarding strategy map).
• Management Information Systems • Baseline queries: Current information-
(MIS) gathering competency needs assessing.
• Geographic Information Systems (GIS) Does the organization have the
• Online Analytical Processing (OLAP) capability of monitoring important
and multidimensional analysis; sources of information? What data does
sometimes simply called "Analytics" the organization collect and how does it
(based on the so-called "hypercube" or store that data? What are the statistical
"cube") parameters of this data, e.g. how much
random variation does it contain? Does
• Real time business intelligence
the organization measure this?
• Statistics and Technical Data Analysis
• Cost and risk queries: The financial
• Supply Chain Management/Demand
consequences of a new BI initiative
Chain Management
should be estimated. It is necessary to
• Systems intelligence
assess the cost of the present operations
• Trend Analysis and the increase in costs associated with
• User/End-user Query and Reporting the BI initiative? What is the risk that
• Web Personalization and Web Mining the initiative will fail? This risk
• Text mining assessment should be converted into a
financial metric and included in the
BI often uses Key performance indicators (KPIs) planning.
to assess the present state of business and to • Customer and Stakeholder queries:
prescribe a course of action. More and more Determine who will benefit from the
organizations have started to make more data initiative and who will pay. Who has a
available more promptly. In the past, data only stake in the current procedure? What
became available after a month or two, which did kinds of customers/stakeholders will
not help managers to adjust activities in time to benefit directly from this initiative?
hit Wall Street targets. Recently, banks have Who will benefit indirectly? What are
tried to make data available at shorter intervals the quantitative / qualitative benefits? Is
and have reduced delays. the specified initiative the best way to
increase satisfaction for all kinds of
For example, for businesses which have higher customers, or is there a better way?
operational/credit risk loading (for example, How will customers' benefits be
credit cards and "wealth management"), a large monitored? What about employees,...
multi-national bank makes KPI-related data shareholders,... distribution channel
available weekly, and sometimes offers a daily members?
analysis of numbers. This means data usually • Metrics-related queries: These
becomes available within 24 hours, necessitating information requirements must be
automation and the use of IT systems. operationalized into clearly defined

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metrics. One must decide what metrics repositories and support analytics that can be
to use for each piece of information exploited at every horizontal and vertical level
being gathered. Are these the best within and outside the firm. BI describes the
metrics? How do we know that? How result of in-depth analysis of detailed business
many metrics need to be tracked? If this data, including database and application
is a large number (it usually is), what technologies, as well as analysis practices
kind of system can be used to track (Gangadharan and Swamy, 2004). BI is
them? Are the metrics standardized, so technically much broader, potentially
they can be benchmarked against encompassing knowledge management,
performance in other organizations? enterprise resource planning, decision support
What are the industry standard metrics systems and data mining (Gangadharan and
available? Swamy, 2004).
• Measurement Methodology-related
queries: One should establish a (Nguyen Manh et.al, 2005) introduced an
methodology or a procedure to enhanced BI architecture that covers the
determine the best (or acceptable) way complete process to sense, interpret, predict,
of measuring the required metrics. What automate and respond to business environments
methods will be used, and how and thereby aims to decrease the reaction time
frequently will the organization collect needed for business decisions. (Nguyen Manh
data? Do industry standards exist for et.al, 2005) proposed an event-driven IT
this? Is this the best way to do the infrastructure to operate BI applications which
measurements? How do we know that? enable real-time analytics across corporate
• Results-related queries: Someone business processes, notifies the business of
should monitor the BI programme to actionable recommendations or automatically
ensure that objectives are being met. triggers business operations, and effectively
Adjustments in the programme may be closing the gap between Business Intelligence
necessary. The programme should be systems and business processes.
tested for accuracy, reliability, and
validity. How can one demonstrate that (Seufert Andhreas and Schiefer Josef, 2005)
the BI initiative (rather than other suggest an architecture for enhanced Business
factors) contributed to a change in Intelligence that aims to increase the value of
results? How much of the change was Business Intelligence by reducing action time
probably random?. and interlinking business processes into decision
making.
10. DISCUSSION
Businesses no longer want what has happened
Any new-form organization now a days but they want to know the underlying reasons.
experience is the value chain, which is set of Rather than knowing how many blankets were
primary secondary activities that create value for sold in December, businesses want to understand
customers. (Denison, 1997) examines several how many were sold in china during a storm. BI
critical activities related to value chain. Without provides unified integrated view of business
effective BI to target process-oriented activities. A retailer knows how many blankets
organizations for supporting, this is not possible. were sold in December across India and
(Davenport, 1993) describes various issues on therefore make better purchasing and stock
re-engineering in business process innovation. management decision for the upcoming year.

Enterprises are building business intelligence
According to (Adelman et.al, 2002), BI is a term systems that support business analysis and
that encompasses a broad range of analytical decision making to help them better understand
software and solutions for gathering, their operations and (Gangadharan and Swamy,
consolidating, analyzing and providing access to 2004) compete in the marketplace.
information in a way that is supposed to let an
enterprise's users make better business decisions. Innovation in data storage technology is now
(Malhotra, 2000) describes BI that facilitates the significantly outpacing progress in computer
connections in the new-form organization, processing power, heralding a new era for real-
bringing real-time information to centralized time BI. As a result, some software vendors with

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superior tools offer a complete suite of analytic business intelligence itself, and a reporting
BI applications, tools and data models that system. The capabilities of BI include decision
enable organizations to tap into the virtual support, online analytical processing, statistical
treasure trove of information. The tools provide analysis, forecasting, and data mining.
easy access to corporate and enterprise wide data
and convert that data into useful and actionable Several varied sectors like manufacturers,
information that is consistent across the electronic commence businesses,
organization—one coherent version of the truth. telecommunication providers, airlines, retailers,
health systems, financial services, bioinformatics
Companies still fee that BI has technology and hotels use BI for customer support, market
related complexities and usable only by research, segmenting, product profitability,
technically savvy specialists. They also feel that inventory and distribution analysis, statistical
BI is expensive. BI takes a long time to yield analysis, multi dimensional reports, detecting
correct analysis. The firms want these analyses fraud detection etc.
in real time for short-term projects. The tradition
BI may not do this but a real time BI Business Intelligence and data mining is a field
environment certainly comes into rescue. Data is that is heavily influenced by traditional statistical
finally treated as the corporate resource in a new techniques, and most data-mining methods will
discipline. Any operational system (including reveal a strong foundation of statistical and data
ERP and CRM) and any decision support analysis methods. Some of the traditional data-
application (including data warehouses and data mining techniques include classification,
marts) are BI, if and only if they were developed clustering, outlier analysis, sequential patterns,
under the umbrella and methodology of a time series analysis, prediction, regression, link
strategic cross-organizational initiative analysis (associations), and multidimensional
(Gangadharan and Swamy, 2004). methods including online analytical processing
(OLAP). These can then be categorized into a
Traditional BI systems consist of a back-end series of data-mining techniques, which are
database, a front-end user interface, software that classified and illustrated in Table 1 (Goebel and
processes the information to produce the Le Grunwald, 1999).

Table 1: Current BI Techniques

TECHNIQUE DESCRIPTION
Predictive modeling Predict value for a specific data item attribute
Characterization and descriptive data Data distribution, dispersion and exception
mining
Association, correlation, causality analysis Identify relationships between attributes
(Link Analysis)
Classification Determine to which class a data item belongs
Clustering and outlier analysis Partition a set into classes, whereby items with similar
characteristics are grouped together
Temporal and sequential patterns analysis Trend and deviation, sequential patterns, periodicity
OLAP (OnLine Analytical Processing) OLAP tools enable users to analyze different
dimensions of multidimensional data. For example, it
provides time series and trend analysis views.
Model Visualization Making discovered knowledge easily understood using
charts, plots, histograms, and other visual means
Exploratory Data Analysis (EDA) Explores a data set without a strong dependence on

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Table 1: Current BI Techniques
TECHNIQUE DESCRIPTION
assumptions or models; goal is to identify patterns in
an exploratory manner
http://www.dmreview.com
In addition, the entire broad field of data mining /article_sub.cfm?articleId=5700
includes not only a discussion of statistical
techniques, but also various related technologies Berson Alex, Smith Stephen and Thearling
and techniques, including data warehousing, and Kurt. (2002) ‘Building Data Mining Applications
many software packages and languages that have for CRM’, Tata McGraw Hill.
been developed for the purpose of mining data.
Some of these packages and languages include: Cui, Z., Damiani, E. and Leida, M. (2007)
DBMiner, IBM Intelligent Miner, SAS ‘Benefits of Ontologies in Real Time Data
Enterprise Miner, SGI MineSet, Clementine, Access’, Digital Ecosystems and Technologies
MS/SQLServer 2000, DBMiner, BlueMartini, Conference, DEST '07.pp. 392-397.
MineIt, DigiMine, and MS OLEDB for Data
Mining (Goebel and Le Grunwald, 1999). Curt Hall. (1999) ‘Data Warehousing for
Business Intelligence’. Retrieved 20 March 1999,
from http://www.cutter.com/itreports/RP68E.pdf.
11. CONCLUSION
Davenport, T.H.(1993) ‘Process Innovation:
Powerful transaction-oriented information Reengineering Work through Information
systems are now commonplace in every major Technology’, Harvard Business School Press,
industry, effectively leveling the playing field for Boston.
corporations around the world. To remain
competitive, however, now requires analytically Denison, D.R. (1997) ‘Towards a process-based
oriented systems that can revolutionize a theory of organizational design: Can
company’s ability to rediscover and utilize organizations be designed around value chains
information they already own. The business and networks?’, Adv. Strategic Management, 14,
intelligence (BI) has evolved over the past pp. 1-44.
decade to rely increasingly on real time data. The
BI systems auto-initiate actions to systems based Gangadharan.G.R. and Swamy, N., Sundaravalli.
on rules and context to support several business (2004) ‘Business Intelligence Systems: Design
processes. These analytical systems derive and Implementation Strategies’, Proceedings of
insight from the wealth of data available, 26th International Conference on Information
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