Business Intelligence Technology - DOC

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					                                                 Business Intelligence (BI)
Business Intelligence has been defined in many ways. Some believe that Business Intelligence is about a
focus on the bottom line, some are focussed on organizational direction and strategic planning, some are
defined as the way of using technologies to help decision making, some definitions focus on using
organizational data through data mining to find out what customers want. Some regard business intelligence
as issues for security and privacy, etc.

In this Chapter, we give a review of existing definitions and propose a more advanced Business Intelligence
definition. We give an overview of 40 years of business intelligence technology in the application
development paradigm. We also give comparisons and contrasts between new age technology such as
Trust and Reputation systems and the existing well known business intelligence tools such as ERP, CRM

We clearly list what new things that the Trust and Reputation systems can do to help business intelligence
and consumer confidence. We describe why Trust and Reputation is a science, why it is a methodology and
why it is a technology and tool for business intelligence. Finally, we give an overview of future research and
development in this new class of technologies.

In the last few decades the use of IT has progressed from provision of infrastructure for handling data,
storage of data, querying data, monitoring, accounting and audit systems to the automation of processes
previously manually carried out by human beings, to providing decision support and more recently to the
provision of business intelligence. Business Intelligence is the new frontier for IT and Business interactions.
Hence it is important that we review and understand its nature and the different elements that go into making
it up.

Business Intelligence (known as BI) can be defined in many ways from many different perspectives. In this
Chapter, we give an advanced definition of Business Intelligence. We shall see how Trust and Reputation
systems can help build business intelligence and consumer confidence. They are different from existing
Business Intelligence applications and tools and they are unique and categorized as new age technology.
We also outline how they are re-shaping e-Business and why they are able to provide customer assurance
and quality of service assessments.

Definition of Business Intelligence (BI)
Business Intelligence (BI) moves away from the traditional concentration by Business on using
data purely for repetitive calculations, monitoring and control to obtaining knowledge in a form that
is suitable for supporting and enabling business decisions from marketing, sales, relationship
formation, fraud detection through to major strategic decisions. In order to understand the nature of
Business Intelligence, we will initially begin by reviewing some of the existing definitions and
notions of BI.
The Classical Definition of BI

In this section, we discuss some well known organizations and their definition of Business Intelligence.

We thought it is useful to look at the definitions not just of researchers but also those put forward by major IT
companies that provide business systems of one kind or another. Such a review of definitions and meaning
ascribed to the idea of business intelligence will understandably not be comprehensive due to limitations of
space. Hence, we have tried to provide a sample that touches on the different threads ascribed to this idea.
Among the companies considered are IBM, Accuracast, Siebel, Cognos and Oracle. A sample of such
definitions is given below.

‘Business Intelligence is a concept of applying a set of technologies to turn data into meaningful information.
With Business Intelligence Applications, large amounts of data originating in many different formats
(spreadsheets, relationship databases, web logs) can be consolidated and presented to key business
analysts.., and armed with timely, intelligent information that is easily understood, and the business analyst is
enabled to affect change and develop strategies to drive higher profits.’ (IBM, 2005)

Copied from Chapter 14: Chang, E., Dillon, T.S., Hussain, F.K. 2006, Trust and Reputation for Service-Oriented Environments - Technologies for Building
Business Intelligence and Consumer Confidence, John Wiley and Sons, UK (400 pages), ISBN: 0-470- 01547-0
Bergerou (2005) citing Accuracast defined Business Intelligence as ‘the process for increasing the
competitive advantage of a company by intelligent use of available data in decision-making. Business
Intelligence consists of sourcing the data, filtering out unimportant information, analyzing the data, assessing
the situation, developing solutions, analyzing risks and then supporting the decisions made’.

Siebel (2005) defines Business Intelligence as ‘a solution suite that integrates data from multiple enterprise
sources and transforms it into key insights that enable executives, managers, and front-line employees to
take actions that lead to dramatic improvements in business performance’. Siebel further considers that the
next generation of Business Intelligence ‘comprises a mission-critical architecture that scales to handle the
largest data volumes and delivers critical information to tens of thousands of concurrent users across the

Cognos (2004) defined Business Intelligence to be event driven. ‘Event Drive BI monitors three classes of
events in operational and Business Intelligence content – notification, performance and operation events –
looking for key changes. Having detected changes, event-driven BI then notifies and alerts decision-markers,
keeping them informed and up-to-minute. This personalized information can be pushed to decision makers
no matter where they, enabling them to make timely and effective decisions’.

Moss and Hoberman [(2005) described Business Intelligence as ‘the processes, technologies, and tools
needed to turn data into information, information into knowledge and knowledge into plans that drive
profitable business action. BI encompasses data warehousing, business analytics tools and
content/knowledge management’.

The Advanced Definition of BI

We see from the above definitions that Business Intelligence refers to the Business understanding its
customers, knowing their needs and wants, studying their purchasing behaviour, identifying potential
services that are in demand, understanding market conditions and reacting quickly, targeting new
businesses, and it is also about learning what we do not know.

Menninger (2005) states that managing the business is about ‘known unknown’ ‘..gather, consolidate,
cleanse and analyze data for purpose of understanding and acting on the key metrics that drive profitability
in an enterprise’ (IBM, 2005) and ‘….Collect data about your business, for analysis and prediction, timely,
easily and decision making capability for an organization at all levels, simplified administration, scalable,
reliable and performance’ (Oracle, 2005).

Taking these factors into consideration, we offer a more comprehensive definition of Business Intelligence as

Business Intelligence is accurate, timely, critical data, information and knowledge that supports strategic
and operational decision making and risk assessment in uncertain and dynamic business environments. The
source of the data, information and knowledge are both internal organizationally collected as well as
externally supplied by partners, customers or third parties as a result of their own choice.

Data is defined as a set of facts about the corporation and its business. Information is an abstraction of data,
which provides semantics about the data with defined meaning, context and value. Knowledge is a high level
representation and abstraction that permits one to reason, carry out pattern recognition, classification,
planning or other high level intelligent tasks and includes representations of uncertainty.

Data can be in the form of sell figures, buyers, suppliers, inventory and budgets, etc. Information can be in
the form of customer demand, cooperation competition, feedbacks, best products, or sell patterns, etc.
Knowledge can be considered as an abstraction of data and information. Knowledge can be obtained directly
from experts or experiences and can also be derived from data mining of the corporate data sources that
provides strategic advice on market trends, profit/loss projections, productivity measurements, quality of
service and product reputation and bottom-line predictions, for which it enables an increase in consumer
confidence and business value.

Copied from Chapter 14: Chang, E., Dillon, T.S., Hussain, F.K. 2006, Trust and Reputation for Service-Oriented Environments - Technologies for Building
Business Intelligence and Consumer Confidence, John Wiley and Sons, UK (400 pages), ISBN: 0-470- 01547-0
14.2.3 40 years of Business Intelligence Development

The following diagram is our view of the 40 years of Business Intelligence development,
together with the associated technology and tools.

                               40 Years of Business Intelligence Technologies and Applications
                                                                                                                 Trustworthiness Systems
                                                                                                                 Reputation Systems
                                                                                                                 Semantic Web and Ontology
                                                                                                                 Digital eco-systems and Tech
                                                                                                                 Quality Assessment Sys
                                                                                                                 Risk Management sys
                                                                                                                 Doc & Text mining
                                                                                          Data Mining            Web Services and Grids
                                                                                          Recommendation Sys Autonomous Agents
                                                                                          Document Handling etc
                                                                                          Information Exchange
                                                      Data Warehouse                      Knowledge Disc/Sharing
                                                      Supply Chain Managemt               OLAP (On-line analytical proc.)
                                                      Decision Support Systems            JIT Services and Track & Trace
                                                      CRM (Customer                       Inter-OP Middleware
                                                      Relationship Management)            Intelligent Multi-agents
                                                      ERP (Enterprise Resource            Security &Privacy
                                                      Planning)                           etc
                                  Business Modelling  KPI (key performance
                                  Workflow Management Index),
                                  Process Control     e-Commerce
                                  Quality Standards   etc.
                                  SLA (Service Level
               Databases         Agreement)
               Inventory Control DBMS, UIMS, etc
               Customer Service
               Account Management
                     1970                    1980                    1990                       2000                     2010

                                                  BI through organization internal data                       BI through organization external data

                                            Figure 14.1 40 Years of Business Intelligence Development Paradigm

The notion of Business Intelligence has evolved over the last thirty years and is likely
to evolve further. This evaluation of the notion of Business Intelligence together with
associated techniques is illustrated in Fig. 14.1.Currently Business Intelligence is
largely focused on the ideas of Data Mining, Recommender systems and Knowledge
Discovery Techniques. These represent very important aspects of Business
Intelligence. However, they are circumscribed by the feature that they conduct this
search for knowledge within organisational databases that either represent useful;
    (a) Information about different aspects & units and individuals within the
    (b) Information that the organisation itself has collected about transactions with
        other organisations and customers.

What they do not allow for is a collaborative notion of intelligence that utilises;
   (a) Knowledge from organizations outside of itself
   (b) Data and information that are provided by customers and other organizations
        as a result of their own choice
   (c) Information arising from the open nature of interactions and the Internet.

Once their new dimensions of interactions and knowledge is added we see that
Business Intelligence in the future will include amongst other things, Trust and
Copied from Chapter 14: Chang, E., Dillon, T.S., Hussain, F.K. 2006, Trust and Reputation for Service-Oriented Environments -
Technologies for Building Business Intelligence and Consumer Confidence, John Wiley and Sons, UK (400 pages), ISBN: 0-470-
Reputation systems, Knowledge Sharing, Ontologies and Ontology based search
engines and internal and external holistic risk management. This is illustrated by the
projected notions of Business Intelligence given in Fig 14.1.

Copied from Chapter 14: Chang, E., Dillon, T.S., Hussain, F.K. 2006, Trust and Reputation for Service-Oriented Environments -
Technologies for Building Business Intelligence and Consumer Confidence, John Wiley and Sons, UK (400 pages), ISBN: 0-470-

Description: Business Intelligence Technology document sample