Abstract
The paper explains that data mining is a process whereby enterprises or organizations in any industry approach their respective data and databases in a more constructive and targeted manner to produce actionable business strategies. As some researchers have observed, data mining and data warehousing are becoming more prevalent because of the large quantities of data stored in various systems and the number of business decisions made based on the data.

From the Paper
"Thus, data mining and data mining techniques have risen to prominence with the elevation in importance of databases and, more recently, the development of data warehouses that have changed the complexion of industry in all sectors. Data mining and data warehousing solutions have been especially important in customer relations management (CRM) and in the healthcare industries for example."

Tags:data, mining, warehouse

Abstract
This paper discusses the process of data mining, in which electronic data is collected, stored in data warehouses, and then culled for specific consumer information in order to understand consumer buying habits to increase business profits and tailor advertising strategies to specific individuals and groups. The pros and cons of data mining are discussed, including the potential for identity theft and fraud.

From the Paper
"Data mining is the process of finding connections between various kinds of data within a large pool, or warehouse, of information. This is a useful process for businesses in that computer technology can be used to sift through and find relevant information amongst large stores of data in order to understanding patterns in consumer's buying practices and use of services (Palace); this information can then help businesses, from marketing and advertising firms, to factories, to the research and design departments of manufacturing companies to increase profits and/or cut costs of producing such goods and services. For instance, if a company..."

Tags:data mining, data warehouses, marketing

Abstract
This paper defines data mining to help senior management to manage and direct the company more effectively. The author points out the types of data. The paper reviews methods of data mining including the software.

From the Paper
"Domestic and global business competition is fierce. Companies must look for new tools to give them a competitive advantage. Technology has added an additional layer of competitive tools commonly called data mining technology or data mining software. For many firms seeking to improve their competitive edge, the ability to perform data mining is rapidly becoming a necessity rather than a luxury. Data mining involves the extraction of hard to find information from large databases that companies normally maintain. Data mining tools can help businesses predict future ..."

Tags:data mining, techniques, tools, models, practical applications, competitive advantage, public and private sector applications, widespread acceptance

Abstract
This paper examines data mining in e-commerce and discusses the various types of modeling used to make the data meaningful to e-tailers. The advantages and pitfalls of data mining and an explanation of how it has transformed e-commerce are detailed. The paper includes an abstract and table of contents.

From the Paper
"Data mining as applied to e-commerce is a breakthrough technology that can gather information in an automated fashion and build models used to predict customer purchasing decisions with remarkable accuracy ..."

Tags:e-commerce, Internet, data mining, personalization, logistic regression

Abstract
The paper considers how data mining was used in the past in the mortgage industry, and how it can be used in the future.

From the Paper
"Companies operating in the mortgage industry collect a vast amount of information about their current and potential future customers. These companies obtain data about earnings, assets, criminal records, spending tendencies, credit history and a host of other things that can provide insight into the consumer's likelihood to successfully repay a mortgage. Financial institutions recognize the value of this data and have long sought ways to take advantage of it to identify patterns that might assist in marketing efforts or prevent loans..."

Tags:data mining, mortgage industry

Abstract
This paper relates that the use of data mining, its adjunct technologies for text mining and the ability to interpret, analyze and create linguistic models from unstructured content is revolutionizing the concept of data mining away from being purely used for structured content in data warehouses to now encompass unstructured content found throughout organizations globally.
The paper then provides insights into various areas of data mining, and the currently high levels of growth analytics use and applications software are experiencing as a result.

Outline:
Executive Summary
Using Data Mining in Business Research
Exploring the principles of Data Mining in Business Research
Predictive Methods in Data Mining

From the Paper
"A second predictive approach is called deviation detection. The purpose of this method is to discover the most significant changes in data from previously measured or median values. An example of the type of use for this predictive approach would be the development of strategies for selling tickets to frequent flyers who booked months in advance versus those that consistently book within a few weeks of their departure. A third approach to using data mining to predict future outcomes is using the classification approach, or technique. This predictive approach of classification uses a collection of records (training set) -- each record contains several attributes, one of them is the class (Ng & Han, 10). The task is to find a model for the class attribute as a function of other attributes, so, after that, previously unknown records can be assigned a very accurate class."

Tags:significant, changes, descriptive, analytics, data, modeling

Abstract
The paper discusses how data mining was employed to customize offerings for goods and services to the paper's author during recent weeks. The paper explains how the avalanche of marketing materials received as a result of data mining can be traced back to many everyday activities. The paper therefore shows that by employing data mining techniques of tracking customer transactions and analyzing the statistical models for anticipated behavior, companies are able to deliver timely, pertinent, and coordinated messages and value propositions to customers and prospects.

Outline:
Introduction
Transactions
Conclusion

From the Paper
"One method for helping a company decide how best to select and interact with customers is to collect and analyze vast amounts of information about people's preferences. The detection and use of statistically relevant patterns to build models that predict customer behavior is the process of "data mining". For a data mining process to be successful, database marketers must first identify market segments containing customers or prospects with high-profit potential. They then build and execute campaigns that favorably impact the behavior of these individuals (Thearling, 2001). This paper will discuss how data mining was employed to customize offerings for goods and services to the paper's author during recent weeks."

Tags:customer, data, tracking, transactions

Abstract
Data mining is the extraction of hidden predictive information from large databases. This paper examines the effect that data mining has on the current corporate climate. It defines data mining and examines the scope of its existence and effects on overall industry and the rest of the world. The paper also explains the basics of the technology behind data mining and how these tools will interact with localized software. Examples of how data mining technology can be profitably used, as well as how it will use the data warehouse architecture to evolve existing software to develop new ways to collect and interpret information, is also looked at.

From the Paper
"Model building itself is not a new technology; it is in fact something that has been around for a very long time. Since the beginning of computer technology, modeling has been a method to finding solutions. Computers work just as humans do by collecting information from a variety of differing situations and attempting to put it together in such a way that makes sense. With computers, there are more resources as well as faster integration of the information so the model building process is easy, fast and efficient. It also is much more complex than anything that a human can build which means the answer is in more depth and more accurate."

Tags:technology, gigabyte, algorithms, warehouse

Abstract
This paper presents an overview of data mining tools commercially available today. These tools are invaluable in helping commercial ventures, scientists, economists, medical practices, and even weather forecasters detect patterns and data sets in vast quantities of information that they have collected. After an overview of what data mining is and how it is utilized, the writer focuses on specific data mining tools on the market. A description of characteristics and the leading products of the type of tool are examined. Finally, a detailed look at a specific product, which uses neural network-based data mining tools, is examined in depth.

From the Paper
"Data mining is the process of seeking and extracting knowledge buried in large volumes of raw data. The importance of collecting data that reflects business or scientific activities is well recognized today. (Brodley, Lane, Stough 1999) Most large and mid range companies now utilize various commercially available data warehousing software for collecting and managing the large quantities of information that they collect. Before data mining technology, the bottleneck in turning raw data into useful information was how to accurately and quickly extract knowledge from the collected raw data. Analysis by humans without special tools cannot make sense of enormous volumes of data that require processing in order to make informed business or scientific decisions. Data mining automates the process of finding relationships and patterns in raw data and delivers results that can be either utilized in an automated decision support system or assessed by human analysts. (Brodley, Lane, Stough)"

Tags:scientist, analysis

Abstract
This paper examines the InfoWorld's article by Paul Krill, "Microsoft Pushes Data Mining in Business Intelligence Protocol" and relates the business merits of Data Mining. The paper also explores other resources on the topic that discuss its impact on business and individuals, with particular attention the Fortune 500 corporations. The paper provides a history of data mining in order to foresee its future.

From the Paper
"There is a great deal of flexibility which businesses who use data mining will have upon their marketing campaigns. By knowing the customer almost as well as the customer knows him or her self, retail businesses can adjust their sales tactics to match the needs and desires of the customers. Individuals will have more choice, and more pleasing choice too. Companies will have more options for enticing customers, and less money can be spent on sending out independent researchers since the data will already be at hand."

Tags:paul, krill, microsoft, xml, soap, information, location, business