The Concept Of Business Intelligence Information Technology Essay

In todays era where the businesses became more competitive and individuals are strive for competitive advantages, a urge for top notch application and technology commenced to be highly in demand. According to Cindi Howson (2008): ” the purpose of BI solution is to assist enterprise users with excellent spreadsheets, reporting, auditing, business strategies and implementations”. In IT, BI is the latest and superior application.

On the other side, R.L. Fielding (2008) remonstrate that information technology is apparently unstoppable and it shows continues greater impact in the business environment as longer as it stays. This is the reason that competition is focused on how to pioneer a stronger information system that could uphold with the competitive environment. The vendors recently constitute the Business Intelligence solution (BI) on its market offerings apart from SAP, ERP, WLAN, PDA and many more.

Concept of Business Intelligence

Most of the organisations emphasizes on data collection and it’s analysis as a cardinal activity for long term strategic planning. Large companies endeavour to gain a competitive advantage over their competition, they uses information management system to analyse their data and these activities have evolved to what is now known as business intelligence of BI.

Fielding (2008) remarked that Business intelligence stages can be divided into raw data, information, and knowledge. First is Raw data, which is gathered and processed into information. The loaded information are filtered and arranged into a purposeful pattern and the data analysis generate the compiled knowledge serves as the business intelligence of the company.

Andy Graham (2008) suggested balance information makes business intelligence most effective. If the data are too little or there is too much input than the data are not useful. Then the organisation could focus on most important improvements they want to implement by putting a reasonable limit on the gathering of information.

Cindi Howson (2008) clarified that “BI can be difficult to structure because an effective BI project teams, develop the right BI applications, manage business-IT communications and measure BI success. Therefore, companies who are trying to immerse into the BI concept should work on to developing and optimizing successful BI applications and get best practices for structuring BI teams and managing business-IT communication” .

The organisation can choose the business intelligence solution in line with their business strategy on the market today. The data warehouses, text mining, data visualization, score carding, and Online Analytical Processing (OLAP) are the most common tools of BI. The benefits of these tools are to sort out raw data and contribute to the formation of effective decision for the company. In a data firm, there are several components of a business intelligence solution from a technology point of view. Data marts, ETL processes, OLAP processes, expert systems, artificial intelligence and fuzzy logics are all parts of the business intelligence solution. A comprehensive business intelligence system must be in place and data must be gathered from internal and external sources to achieve the business objectives. That makes the business intelligence most important part of any organisation’s strategy.

Business intelligence Process

1. Extracting information from the necessary source systems such as ERP, CRM, POS, ATM and

different file systems

2. Captured information extract, transformed and load into a repository such as a data mart or data warehouse.

3. From data ware house, user enable to get answers of specific types of business questions

4. To make the business decision reporting and analytical tools are used to analyse the information, these includes ad hoc reporting, OLAP, dashboards, alerts, predictive models.

The artificial intelligence system

The artificial intelligence system deals with the machines, help them to find solution to multiple and complex problems in a more human like fashion. Artificial intelligence system is concerned with two basic ideas. (cawsey et al., 1998) First it involves perusing the thought process of humans; second it deals with representing those process via machines. It has the capabilities to assist in fighting terrorism(kahn, 2002) that create more attention towards it and another is the large number of intelligent devices available in the marketplace. (Rivlin, 2002).

Artificial intelligence is the branch of computer science that deals with the way of representing knowledge. It uses symbols rather than numbers, and heuristics, or rules of thumb, rather than algorithms for processing information.

Human experts gives knowledge that consists of as facts, concepts, theories, heuristic methods, procedures and relationship to computer as it cannot have experience or study and learn as a human can. Knowledge is also information organized and analyzed to make it understandable and applicable to problem solving or decision making. Knowledge base stored and organized collection of knowledge related to a specific problem to be used in an intelligence system.

Advantages of AI

1. AI application makes computer easier to use and can make knowledge more widely available.

2.AI significantly increases the speed and consistency of some problem solving procedures in comparison of conventional computing and incomplete data or nuclear data.

3. It significantly increases the productivity of performing many tasks; it helps in handling information overload by summarizing or interpreting information and by assisting in searching through large amounts of data.

Expert system

Definition- Expert system is a computer programme that mimic the thought process of a human expert to solve complex decision problems in a specific domain. Expert system either support decision makers or completely replace them. (Edwards et at.2000)

The basic idea behind an ES is to transferred expertise form an expert to the computer. This knowledge is stored than in computer for specific advice enables to users. Four activities involves in transferring expertise from an expert to a computer and then to the users. Knowledge acquisition(from experts), knowledge representation (in the computer), knowledge inferencing, and knowledge transfer to user. Acquired knowledge from experts filtered through the activity of knowledge representation after then acquired knowledge is organised as rules or frames and stored electronically in a Knowledge base. Given the necessary expertise stored in the knowledge base the computer is programmed so that it can make inferences. The inferencing is performed in a component called the inference engine, which is the brain of the ES and results in a recommendation for novices. Thus the expert’s knowledge has been transferred to users.

The components of expert system

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1. The knowledge base contains knowledge necessary for understanding, formulating and solving problems by two basic elements facts and theories. Facts such as the problem situation and theory of the problem area; facts that direct the use of knowledge to solve specific problems in a particular domain.

2. User engine is the brain of ES and that applies the axiomatic knowledge in the knowledge data base to the task specific data to arrive at conclusions.

3. The user interface is like a code that controls the dialogue between the user and the system. The dialogue triggers the inference engine to match the problem symptoms with the knowledge in the knowledge base and then generate advice.

4. The explanation subsystem can trace responsibilities for arriving at a conclusion and explain the ES’s behaviour by interactively answering questions.

Benefits of Expert system

1. Increased the consistency, frequency and probability in decision making.

2. Human expertise can be distribute

3. Expedite real time, cost effective and expert level decision by the non-expert

4.Allows impartiality by weighing evidence without bias and without regard for the user’s personal and emotional reactions.

5. Embellish the utilization of most of the available data.

6. With the use of expert system, human expert can get the time to concentrate on other important activities.

Other intelligence systems

Natural language processing (NLP) is refers to communication with a computer in English or whatever language you may speak

Speech recognition and understanding is a process that allows us to communicate with a computer by speaking to it. when a speech recognition system is combined with a natural language processing system, the result is an overall system that not only recognizes voice input but also understands it.

Voice synthesis-the technology by which computer speak is known as voice synthesis.

Artificial neural network (ANNs)

Fuzzy logic deals with uncertainties by simulating the process of human reasoning, allowing the computer to behave less precisely and logically than conventional computer do.

Web based management support system (MSSs) that can benefit both user and developers. These system include decision support system of all types, including intelligent and hybrid ones.

Amazon and intelligence system

Amazon uses information system in collecting data in 3 ways

1. Operational data- The company collects this data from automated programs that are built into the web site. The inbuilt programs gather information such as conversion rates, number of clicks per visitor, profit per converted visitor and every other move a consumer makes on the website. (Chaffey et al, 2006). And using predictive analysis Amazon offers recommendation for its potential buyers.

2. Tactical data -Amazon.com uses this type of data and automates customer channel preferences, the way the web is displayed to different users as well as merchandising and recommendations. It also use this data for its key features such as “your recommendation” and its personalised e-mail programme, which manage and keep track of e-mails sent to specific groups of customers.(Chaffey et al. 2006). These activities carried out by using predictive analytic model incorporating with tactical data.

3. Strategic data- Using this data Amazon determine which products are profitable and which products needs to be discounted. It also uses this data for its free shipping campaign.