Data Fusion and Data Mining - Research Paper Example

At a period when computer technologies are very vital tools to business, every new and emerging technology to gain better market share. Ever since the dawn of the web and its prolific use in selling and promotions, marketers aim to acquire the latest technology to outsmart competitors and to dominate the market. They see to it that they will be the first ones to fully utilize every fresh innovation that have arisen in the computer technology world. One of the fertile areas in computer science that marketers want to exploit is in the area of data collection and management. Every day millions of data are being transmitted by the use local area networks and the Internet. Aware of the voluminous demand for data storage, computer manufacturing firms regularly innovate file storage devices. They introduce new and more “intelligent” devices and gadgets to cope with this ever-escalating demand for storing and retrieving data. Despite their success in solving the data storage problem, companies are still hoping to use technologies that will provide them clear information on what really is going on in their businesses. Storing and retrieving myriad chunks of data are not enough to solve pressing business problems. Businessmen need useful information out of these. Owning data warehouses have partially solved this problem. A data warehouse is used to consolidate data found in different databases. This makes millions of data easily retrieved, interpreted, sorted and accessible by analysts. Though this device largely helps analysts, sorting and storing data are not enough to make most out of these data. They still cannot provide us a clear picture on what is really going on in the firm and in the market (Alexander, n.d.). Data Fusion and Data Mining Turning numerous data into significant information is the aim of one of the latest technological breakthroughs in computers known as data fusion and data mining. These technologies enable firms to automatically search millions of data that they receive every day “for patterns using tools such as classification, association rule mining, clustering, etc. (Data Mining, 2007).” Data fusion is the method of integrating “diverse data into a single, coherent representation of the tactical, operational or strategic situation (Cyr, 2006).” We can say that data fusion is the first step in data mining. To find patterns, one should consolidate huge chunks of data to find out their similarities. This is exactly what data fusion is doing. Data mining divulges strategic hidden patterns found in huge amounts of data using high-end data analysis methods. It discovers new knowledge instead of testing assumptions that are suggested by users, which are being used by other business intelligence technologies (Sentient Information Systems, n.d.). It is an automated technology that allows exploration, analysis and visualisation of data of very large databases. Having the power to extract novel, implicit and actionable knowledge from large datasets, data mining are used for the discovery of non-obvious and finding out information and knowledge that can develop business processes. Uses of Data Mining in Sales and Marketing Having powerful capabilities makes data mining a very useful tool in business. It is used in sales/marketing, customer retention, buyer behaviour, costing, quality control, inventory, and fraud (Williams, Hegland, and Roberts 1998). In sales and marketing, data mining enables businesses to improve market segmentation by identifying noticeable characteristics of customers who buy identical products from the same business. In an ice cream bar, for example, data mining can point out that 12% of the customers aged 5-10 prefers ice cream cones chocolate toppings during Fridays. The bar’s marketer can declare Friday as chocolate day in his stores. Upon knowing the subtle characteristics that largely affects buying habits, it can also predict which customer will most probably stop availing one’s products/services and transfer to a competitor. With the its predictive power to analyse trends, data mining can give us hints on what characteristics of a product can repel customers from buying one product. Data mining can also identify which prospects should be picked in a mailing list to get the highest response rate. To get the most desirable outcome in a survey or in a poll, marketers can strategically create select which among their existing customers will most likely give them their desired responses. Predicting the most probable part or element in a website that a web surfer is interested in seeing is another function of data mining. This also applies to any other business. The power to pinpoint which specific elements or things that can greatly affect the saleability of a product. Through this technology, businesses can also point out what combinations of products/ services in a market basket are commonly bought. For example, in an e-store, a marketer can point out, through the use of data mining program, that 10% of buyers prefer buying computers while eating chocolates. Data mining can also provide a trend analysis that reveals the difference between last month’s typical customers to the next. Aside from these capabilities, data mining can also provide fresh business opportunities by automating the prediction of trends and behaviours of customers and by discovering previously unknown patterns (Alexander, n.d.). All-in-all marketers can use data mining to accomplish these three important goals: to seek and retain most profitable customers, to segment markets for a targeted approach, and to predict future processes and to identify factors to secure a desired effect (SAS, 2007). Companies Using Data Mining Because of its immense power, MIT Technology Review selected data mining as one of the 10 emerging technologies that will “change the world (Konrad 2001).” Aware of virtually unlimited possibilities that this phenomenal technology does, numerous companies has empowered it into their systems. This is the reason why Amazon.com peddles other seemingly unrelated products after a customer clicks on a particular item. By analyzing millions of data that Amazon.com receives from its online consumers, data mining programs were able to point out which products are most likely bought alongside the product that the customer is about to buy. Other companies, such as eGiftbasketstogo.com and AtlantaCarsInc.com use data mining to track down the progress of their business. “Tracking to a merchant is as important as the instruments on a plane to a pilot, Tom Bianco, the CEO of these two companies said. His use of free analytics program offered by search sites cut his ad expenditures. Instead of placing multi-million advertisements without much assurance that it would really address the target market, Bianco uses data mining in predicting buying trends that can reveal where his target customers is and how to access them (Regan, 2007). Critiquing Data Fusion and Data Mining Data mining offers us huge amounts of opportunities to improve business. It can reduce financial and even opportunity costs. It can also be a method to track down criminal elements and can also be used to prevent disasters from taking place. The National Security Agency of the United States has divulged that they have “massive database of American’s phone calls” to thwart the possibility of another 9/11 attack (Cauley 2006). However this also questions the right of anyone, including the US government to invade privacy of others. Due to its enormous capability to give meaning to data, data mining can be an instrument to extract confidential and private knowledge. The constitutional right of a person to secure his freedom of privacy can be invaded by the intrusive power of data analysis. Its meddling capacity can also put not only the security of a firm but also of a nation as a whole at risk. Mining data is equivalent to basking into the elements and information that the data really hold. If this technology would be owned by criminals, it can create unspeakable acts of inhumanity and terror. Just imagine the gravity of destruction that the terrorist can do if they use this advanced technology to perpetrate their evil schemes. Just like a marketer points out the hidden buying patterns of the company’s customers, a terrorist can also predict when the most devastating time to execute their terror will be. Thus the governments of all nations in the world should protect this profitable technology to prevent innumerable loss. References Alexander, Doug n.d. Data Mining [online] Available from: http://www.eco.utexas.edu/~norman/BUS.FOR/course.mat/Alex/ [cited 26 April 2007] Cauley, Leslie. 2006. NSA has massive database of Americans’ phone calls. USA Today. [internet]. Available from: http://www.usatoday.com/news/washington/2006-05-10-nsa_x.htm. [cited 26 April 2007]. Cyr, J. 2007. Glossary D. Space and Electronic Warfare Lexicon. [internet] . 25 April. Available from: http://www.sew-lexicon.com/index.html. [cited 26 April 2007]. Konrad, Rachel 2001. Will data mining revolutionize e-commerce? CNet News [internet]. 08 February. Available from: http://news.com.com/Behind+the+numbers/2009-1017_3-252162.html. [cited 26 April 2007]. Regan, Keith 2007. Data Mining for E-tail Gold. Tech News World. [internet] 20 April. Available from: http://www.technewsworld.com/story/56975.html [cited 26 April 2007]. SAS Institute, Inc.2007. Data and Text Mining [online] SAS Institute, Inc. Available from: http://www.sas.com/technologies/analytics/datamining/ [cited 26 April 2007]. Williams, G., Hegland, M., & Roberts, S. 1998. A Data Mining Tutorial. [speech]. 14 December. Presented at the Second IASTED International Conference on Parallel and Distributed Computing and Networks (PDCN ’98) Available from: http://wwwmaths.anu.edu.au/~steve/pdcn.pdf. [cited 26 April 2007]. Read More