Data mining, a process that involves the extraction of predictive information which is hidden from very large databases (Vijayarani & Nithya,2011;Nirkhi,2010) is a very powerful and yet new technology having a great potential in helping companies to focus on the most important data in their data warehouses. The use of data mining techniques allows for the prediction of trends as well as behaviors thereby allowing various businesses to make proactive and yet highly informed knowledge-driven decisions. Data mining can therefore help businesses in answering various business questions that in the past have been considered too time consuming to analyze and solve. Companies can therefore collect as well as refine large quantities of data in order to gain a competitive advantage from the hidden predictive patterns contained within. In this paper we determine benefits of data mining to the businesses when employing:
Predictive analytics to understand the behavior of customers
Associations discovery in products sold to customers
3. Web mining to discover business intelligence from Web customers
4. Clustering to find related customer information
The paper also assesses the reliability of the data mining algorithms and then decides if they can be trusted and then predict the errors they are likely to produce. An analysis of the privacy concerns raised by the collection of personal data for mining purposes is also conducted.
Benefits of data mining to the businesses
The benefits of data mining to businesses are numerous. The high level of competition in the global marketplace has forced companies to seek out various competitive advantages aimed at reducing or eliminating inefficiencies, maximizing relationships with all the relevant stakeholders as well as optimizing internal operations. In order to help in this endeavor, companies are involved in the development as well as deployment of effective data mining technologies aimed at leveraging the data resources in order to enhance their decision making capabilities as noted by Nemati and Barko (2003).data...
Data Mining The amount of knowledge available in today's world is massive. The information technology specialist who's responsible to his or her organization for maximizing the capacity for practical usage of this knowledge, it is becoming increasingly difficult to have a total grasp of the problem. The purpose of this essay is to discuss the importance of implementing data warehousing and mining systems inside an organization. In order to do this,
Data Mining in Health Care Data mining has been used both intensively and extensively in many organizations.in the healthcare industry data mining is increasingly becoming popular if not essential. Data mining applications are beneficial to all parties that are involved in the healthcare industry including care providers, HealthCare organizations, patients, insurers and researchers (Kirby, Flick,.&Kerstingt, 2010). Benefits of using data mining in health care Care providers can make use of data analysis in
Data Mining Determine the benefits of data mining to the businesses when employing: Predictive analytics to understand the behaviour of customers "The decision science which not only helps in getting rid of the guesswork out of the decision-making process but also helps in finding out the perfect solutions in the shortest possible time by making use of the scientific guidelines is known as predictive analysis" (Kaith, 2011). There are basically seven steps involved
Data mining on Coronary heart disease Data mining, also known as data discovery and data knowledge is the process of analyzing hidden patters of data using the specified approach desired in order to extract useful information, collected and assembled into common topics for effective analysis to facilitate decision making (The Economic Times, (2018). This approach can be used in trying to determine whether there is a common trend in the genetic
Data Warehouse and Business Intelligence In order to write a paper on the similarities and contrast between data warehouse and business intelligence, we need to first define each term before finding the similarities and contrasts between the two. Data Warehouses Data warehouse are used for storing data for archival, analysis, and security purposes. The warehouses themselves are made up of one or many computers (i.e. servers) that are connected together into one giant
In addition to these two Director-level positions, the roles of the users of the databases and data mining applications also need to be taken into account. The sales, marketing, product management, product marketing, and services departments all need to have access to the databases and data mining applications. In addition, branch offices that access the company's applications over the shared T1 line will also need to have specific security
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