Data Mining
Businesses can receive many benefits from data mining. Which benefits they receive, however, can also depend on the way in which their data mining is undertaken. Predictive analytics are used to understand customer behavior, and businesses use the behavior of the customer in the past to attempt to determine what the customer will do in the future (Cabena, et al., 1997). While it is not an exact science, many companies believe they can use it in order to decide which products will sell most often to which customers (Nisbet, Elder, & Miner, 2009). Association discovery is another type of data mining, and is more involved with the products that are sold and how they match up to specific types of customers, as opposed to specific customers by name or other determination (Nisbet, Elder, & Miner, 2009). In other words, predictive analytics look at what customer A will buy again, but association discovery looks at what customer A will buy based on his belonging to a particular group of customers who also buy a particular product.
Web mining is used to discover information about customers on the web (Hastie, Tibshirani, & Friedman, 2001). Club cards that are used to access a company website, for example, can help a customer be tracked and his or her spending and buying habits can be discovered. Customers may not always realize that this is going to take place, but it is the only way that companies can provide "for you" deals for specific customers who are part of their rewards structure. They have to know what the customers are routinely buying in order to know what to suggest to them. Clustering is yet another way of data mining, and it looks for customers who are related in their buying habits (Nisbet, Elder, & Miner, 2009). If a particular kind of customer buys certain things very often, then it stands to reason that other customers who also appear to be the same kind would buy those same things. Of course, like any kind of data mining it is not an exact science. There are many things that can affect...
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 is very important for operational effectiveness but when / how to stop mining data before it becomes more trouble than it's worth? Over the last several years, advancements in technology have meant that an increasing number of companies are using data mining to be able to understand the demographics of their customers. This is when they will look at large amounts of information to figure out specific buying habits
Growth Aided by Data Warehousing Adaptability of data warehousing to changes Using existing data effectively can lead to growth Uses of data warehouses for Public Service Getting investment through data warehouse Using Data Warehouse for Business Information Ongoing changes in Data Warehousing The Origin of Data Warehousing and its current importance Relationship between new operating system and data warehousing Developing Organizations through Data Warehousing Telephone and Data Warehousing Choose your own partner Data Warehousing for Societal Causes Updating inaccessible data Data warehousing for investors Usefulness
Loyalty Programs Popularity of loyalty programs is increasing, both in terms of the number of programs offered by merchants and in participation by customers. Yet, it seems that both groups remain ill informed of how the programs actually work and the true benefits and costs. This paper explores the reality of loyalty programs and concludes that they can be beneficial for all parties provided that they fully understand what the programs
2% of the population is younger than 14; 58.2% is aged between 15 and 64 and 3.6% is over the age of 65. This affect Giam's in a positive way as most of the population is properly aged to work The median age of the population is 20.2 years, with 19.9 years for men and 20.4 years for women The birth rate is of 29.85 births per 1000 individuals The death rate is
Business Ethics Focus on Merrill Lynch According to Laura Hartman and her co-writer, Joe Desjardins in the work entitled "Business Ethics: Decision Making for Personal Integrity & Social Responsibility" philosophical ethics may be clearly differentiated from theological ethics because theological ethics attempted to disseminate the well-being of an individual on a religious basis while the ethics of an individual's philosophy is such that provisions of justifications that can be applied to
Our semester plans gives you unlimited, unrestricted access to our entire library of resources —writing tools, guides, example essays, tutorials, class notes, and more.
Get Started Now