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 etc.
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) d efines 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 enterprise ’.
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 follows.
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.
Business
Intelligence
40 Years of Business Intelligence Technologies and Applications
Business Modelling
Workflow Management
Process Control
Quality Standards
SLA (Service Level
Databases
Agreement)
Inventory Control
DBMS, UIMS, etc
Customer Service
Account Management etc
Data Warehouse
Supply Chain Managemt
Decision Support Systems
CRM (Customer
Relationship Management)
ERP (Enterprise Resource
Planning)
KPI (key performance
Index), e-Commerce etc.
Quality Assessment Sys
Risk Management sys
Data Mining
Recommendation Sys
Doc & Text mining
Web Services and Grids
Autonomous Agents
Document Handling
Information Exchange etc
Knowledge Disc/Sharing
OLAP (On-line analytical proc.)
JIT Services and Track & Trace
Inter-OP Middleware
Intelligent Multi-agents
Security &Privacy etc
Trustworthiness Systems
Reputation Systems
Semantic Web and Ontology
Digital eco-systems and Tech
1970 1980 1990 2000 2010
BI through organization internal data BI through organization external data
Time
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 organisations.
(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-
01547-0

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-
01547-0