Free «Business Intelligence» Essay

Business Intelligence

BRIEF INTRODUCTION

The modern era is full of technological advances whose life cycle keeps changing each passing day. Business organizations have thus not been left behind in the evolving planet. As a matter of fact, information is power. Organizations, mainly in business related fields, have to keep up with the pace of their competitors. They definitely cannot withstand the stormy weather without masterminding themselves past their weaknesses and probably inflating more into their strengths. Business intelligence is increasingly becoming a more and more popular tool among business players. Business intelligence is a constituent of tools used in acquisition and analysis of data (Williams & Williams 2010). The systems employed will usually aid in displaying the progress of a given business’ intelligence in areas like customer support, customer profiles, a given market segmentation, profits and statistics, etc. Business intelligence is normally made possible by use of sophisticated software that simplifies data mining by making easier to retrieve information.

IDENTIFYING  BUSINESS CASE PROBLEMS,ANALYSING THE PROBLEMS IN DETAIL AND PROVIDING THE NEEDS FOR APPLICATION OF ARTIFICIAL INTELLIGENCE ON THE PROBLEMS

Economic recession is viewed as one of the major threats to the world at the moment. Consequently, a lot of organizations are facing a fight to survive the patchy path. Cost of production has shot severely. All the factors of production such as land, labour, capital are becoming more and more expensive. Economic meltdown has directly demanded that even the cost of hiring workers has to increase. Human resource departments in many of the organization are experiencing a great challenge in acquisition of cheap labour. It is important to have balance between costs of production and profits to be generated. To single out the difficulties experienced, let us just consider an example of one factor of production that is increasingly facing inflation in terms of cost, labour. Escalating cost of production in developing countries or third world countries that were previously deemed the cheapest source of labour has really dealt lots of businesses a blow. Let us take an example of two factories that are in business to supply milk to consumers in the vicinity. For any of the two business enterprises to compete favourably with the other, it has to attract customers. Lowering the price of the commodity is one of the options at hand. How then can an enterprise be able to lower the cost of the commodity without creating an imbalance with the required production costs? This is where artificial intelligence comes into practice. A firm has to employ modern techniques to lower the costs needed to facilitate a given production process (Gerrard 2008).

At this juncture, business intelligence can be employed to study all the factors of production and challenges. Their value in business today can no longer be underestimated. One may simply term them as simply priceless. It will, therefore, be of essence that an entrepreneur takes his or her time trying to take information in a bid to quantify the factors and even to assess the quality of the factors that are to be employed. Knowing the essence of the latter, it will be wise enough for us to practically display how technology can act as a stepping stone towards success in the business (Williams & Williams 2010).

For analysis, a case of an online dealing foreign exchange trading brokerage firm will be considered. Forex trading is said to be the largest business trading in the world. The popularity of the trading brokers rise every day. The company invites customers to participate in Forex by simply investing a small amount in them. Such company will reap profits through the online traffic and directly from the exchange it participates in. However they face lots of limitation in their day to day running of activities.The most notable challenge is voltatilty: the currency values are dynamic. Competition is also another challenging factor in Forex business. Such a company will have to attract lots of customers for it to profit better than its competitors (Kuyda & Hotproff 2001). To optimize profits for the company, all stakeholders and shareholders should be left hands tied. Our best bet will be to build business intelligence on some of the company’s problems cited. In our case, artificial intelligence sotware will serve the purpose of facilitating human resource management efficiency, picking out efficiency in the trade market, learning from market trends and improving on them and so on and so forth.

CONCEPTUAL FRAMEWORK FOR USING BUSINESS INTELLIGENCE IN DEALING WITH THE PROBLEMS IDENTIFIED

First, we will gather the relevant data required by the company. Raw data is considered an important building block towards achieving a successful intelligence system. Otherwise with no data where else will we retrieve the finished product. Such a company will require sophisticated methods of keeping track of customer details, employee details, and lastly, but most importantly, the Forex details. The company must deliver results. Working at Forex is not that easy as witnesses may confess. Lots of technicalities are involved for such company to succeed. Customers demand quality and not ask for it. This is usually termed as the extranet environment whereby customer interaction with employees is highly regarded. Such connections can assist in developing formidable relationship with other probable suppliers and business partners in related fields. A highly attractive website with a top rated domain will also serve to boost the connection between customers and the Forex masters (Robert 2001). More stable internet connection not only serves for an improved customer service but for the purpose of Forex trading. Minute by minute information on the market will be needed, thus information will be delivered to the experts on time and timely profit generating decisions will be made that will benefit the company in question.

The tricky part of business intelligence is probably designing of its infrastructure. The fact that business is expected to grow makes it more complex to create its systems and thus experts should be able to see beyond their noses when designing such fabricated systems. A clear example is the expected rise in the number of customers trading with the Forex Company. A designer should be able to design a database that will be able to accommodate all of the expected number. Predictive nature of experts serves to avoid crashing of very expensive database components, for example, site failure, thus saving gigantic sums for the company (Rud  2009).

Storage of data from the required sources in the company should be kept in a warehouse. Key components in the Forex Company should be identified for a correct architectural design of the warehouse to be achieved (Thierauf 2001). The key components are like customer details, Forex market details, Employee details to name just a few. The correct layer of the database will then be constructed from the information achieved from the organization. A more pronounced layer in the database in normally the application layer (Blockdjik 2008). The above company that is the Forex Company like any other company requires timely report generation and disbursement to consumers. Emerging trends in the market either in the Forex market or in the general market should be noted from database querying and analysis that involves tools like graphical analysis tools. The application layer should have the capability to give employees and consumers easy access of the trends. For a company that deals with foreign exchange, a probable idea would be to build a mobile phone application that makes retrieval of information stored in the company’s database easy to access. This can be of great benefit particularly to customers. Prompt decisions can be made this way. As somebody once put it, it is important to increase customer loyalty by providing information on accounts if they are to make faster great investment strategies.

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Is it possible then for us to reduce the factors of production and maximize our profits? Yes it is. Taking the case scenario above an intranet would be an ideal way of showing how an organization can cut its cost of production (Veccelis 2011). If the Forex Company sets up a networking among its employees flow of information in the organization, then it will be multidirectional. This is opposed to the classic way of transfer of information, whereby movement of information was linearized (Loshin 2000). The latter thus saves a fortune for the company that would otherwise depend on messengers to relay information. It also saves time for the business. Time is really money for such an organization that highly depends on spot on decision making.

BUSINESS INTELLIGENCE METHODS TECHNIQUES FOR DEALING WITH THE PROBLEMS IDENTIFIED

Advanced business intelligence methods are needed to create business analysis concepts that are the main aspect of why people built them in the first place. One tool needed is data mining. Data mining is a term used to a process whereby one can visualize patterns and trends from a set of data availed. Successful organizations have the ability to note important trends from the information stored in a warehouse. A Forex expert should note trends from the market and determine when and when not to play his cards. Lots of entrepreneurs have lost huge sums of money due to negligence, especiallly in matters that involve currency trading (Vitt & Luckevich 2008). Data mining play a role in prediction of the future trends, classification of similar events, showing information according to the value predicted and so on and so forth.

One other priceless aspect of business intelligence is the online analytical processing (OLAP). It is normally defined as the ability to manipulate queries and analyse data from different set of angles. Through OLAP data queries can be made faster than ever before (Mary 1999). Data warehouses should be configured in a multidimensional way which makes it fast for a person to achieve even complex queries. This is unlike the rational databases and the online Transaction processing. As cited, a company dealing in Forex will highly benefit from such a database. Faster retrieval of information will earn them more money and save them a lot too. Employees involved in the trade will easily be able to note the trends by navigating through the database looking for a specific subset of data. The analyst can be able to perform operations on the data depending on his or her desires. Such operations include performing slicing and dicing of the data, pivoting, nesting, drilling up and down.

Predictive analytics is another business intelligence tool being employed these days (Steve 2010) .To shed more light on the method; it basically entails ability to predict the future. Business auctioneers, for example the Forex entrepreneurs, should always employ the tool to avoid failures in the coming periods. All the variables of a business are entailed in a predicative analysis. Mathematical formulae are used to predict the future (Zorilla et al. 2012).This is made possible by employment of algorithms like linear regression model, time regression model and multinomial model. Such models provide a yard stick of what is to be expected of the future. Their accuracy depends highly on the number of variables that are plugged into the function. The more the variables are used, the less the accuracy. A business like the foreign exchange business can be able to predict their future income using data available from data marts and data warehouses. Predictive models are models related to the predictive analytics but only differ in that it mainly dwells on past data. The benefits of the two methods tend to be more or less the same. Common business techniques present in modern business environments are tabulated below.

BUSINESS TECHNIQUE

             DESCRIPTION

Model visualization

Employing statistical tools like charts, histograms and graphs to gain information.

Exploratory data analysis

Neglecting data dependence and models and exploring the data items.

Online analytical processing

Analysis of multidimensional data.

Temporal and sequential data analysis

Establishing trends and periodicity.

Classification

Establishing where a data item belongs.

Clustering and outlier analysis

Grouping of data into classes whereby data with same characteristics are placed in one class.

Link analysis

Showing a correlation between a set of attributes.

 Descriptive data mining

Dispersion or distribution of data.

Predictive modelling

Foresee a value for a specified data item.

CONCLUSION

There is no doubt that appropriate technology is a necessity in modern business organizations to improve competitiveness in the ever dynamic business world. Business intelligence can maximize profits given by a particular business enterprise. Challenges like economic meltdown can be broken down by use of such result optimization techniques. The future is highly dependent on technology if we are to reduce some of the problems that humans have been predisposed to particularly in the 21st century.

 

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