Abstract Data mining has become a very important concept today and is used by companies all over the world to increase their profits and target the right market. The paper talks about the different aspects of data mining, tools used, and future trends in data mining. Data mining benefits are discussed in detail, and an entire discussion related to the trends in data mining is presented.
1-Background
2-Introduction
3-Data Mining Growth and Tools
4-The Data Mining Process
5-Data Mining Market Place Trends
6-The Data in Data Mining and Meta Data 7-Types of Data Mining Problems
8-Privacy and Ethical Sensitivity in Data Mining Results
9-Future Prospects of Data Mining
10-Works Cited
From the Paper "Data, particularly in the vast diversity and immense quantity that it is available to modern business, was till recently almost very hard to find and understand. Yet, the comprehension of data is the most crucial step to extracting the knowledge that it contains. The scenario has drastically changed today where data is much more easily available and has become more "meaningful" with the utilization of Data Mining. Today, technology offers business managers powerful new tools for gleaning knowledge from data-the essentials of data mining. Data mining has become increasingly important to mainstream companies to become more competitive both in their workings and their customer based relationships. Data mining, as such is of great interest because it is imperative for organizations to grasp the competitive value of information contained within their data repositories. There are a number of pertinent benefits of data mining. First of all, data mining provides the tools and techniques that are essential for optimization of customer relationships. Secondly, data mining provides an automatic method of discovering patterns in data. Thirdly, but not the least, data mining tools can identify the relationships that are actually present in historical data."
Abstract This paper explains that this research study explores how consultation, information, diagnosis, treatment and other aspects of holistic health care services could be successfully provided via the Internet in a remote region of South Africa. The author points out that the purpose of this study is to assess the needs and characteristics of the web portal ,such as desired features, ease-of-use, and understandability and functionality, as viewed by patients/clients. The paper relates that the methodology of this study is both qualitative and quantitative with the data collected through questionnaires, which are included in the paper. The paper also includes tables.
Table of Contents:
Executive Summary
Project Goal
Requirements of System Design
Focus of Project Research and Design
Overview of Project
Design Details and Specifications
Website Study Design
Overview of Findings of Study
Introduction
Background to the Study
Importance of the Study
Focus of the Research
Research Design
Data Collection Analysis
Resources
Project Schedule
Risk Assessment - Project Limitations
Research Methodology
Quality Assurance Factors Of The Study
Background Research
Data Required
New Skills
Design Method
Technology Used (I.E. Software, Hardware, Etc.)
Literature Review
Methodology
Statistical Analyses
Initial Survey/Questionnaire
Post-Patient Survey/Questionnaire
Conclusion
Results and Findings of the Study
Discussion
Recommendations
From the Paper "The natural health practitioner's practice is quite different from that of medical doctors in that much of the homeopathy is based upon the patient's response to questions posed by the practitioner. Consultations require a one-hour period of time limiting the number of patients the practitioner is able to see in a day. Another means of conducting consultations would prove to be invaluable in terms of healthcare delivery to the patient base of this clinic. This system would furthermore allow quicker feedback and results to be filtered to the patients and would end the incessant waiting until their next appointment to receive results, feedback or instructions for their healthcare needs."
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."
Abstract This paper describes that data structure is a way of storing data in a computer so that it can be used efficiently. The paper then goes on to describe how computers store the said data in terms of binary data presentations using Boolean logic. Furthermore, the paper describes data in the form of bits, along with converting binary data into decimals. Lastly, the paper talks about a computer's physical memory, which is based on one of two systems: (1) Random access memory (RAM), or (2) Read-only memory (ROM), and goes on to talk specifically about different coding systems.
From the Paper "Data directly supported by CPU are called primary data type or machine data type computers. CPUs also process complex data type such as string, array, text files, databases, and image data such as MP3, jpeg, and mpeg. However, 64-bit and the 128-bit use different math functions in order to maintain portability. In each case, there is a signed and unsigned integer type associated with each. Excess notation is a format that is used to represent a signed integer and represents numbers in order and at the transition point; the high-order bit is set at zero. This represents the excess number. Positive numbers are above in order, negative below (Burd 78). Zero represents the excess identifier therefore; the excess 16 notation shows the value for zero is the bit pattern for 16 that is 10000."
Tags: RAM systems, data structure, software, boolean logic, memory
Abstract This two-page paper presents a discussion about two companies and their products. The writer takes a look at EMC and Network Appliance, Inc and presents an overview of their product, their innovations and other information.
From the Paper Network Appliance, Inc. is a company that is engaged in the business of network attached data management and storage solutions. As the technological world continues to advance the ability to share and store data on a broad scale level becomes increasingly important and the Network Appliance Inc goal is to provide the means to handle the need.
?Network Appliance hardware, software, and service offerings are used to create, manage and scale seamless data fabrics, moving information to users globally. The Company's products consist of filer storage and caching appliances, data management and content delivery software, and support services. Network Appliance storage appliances, or filers, are systems that provide highly reliable data storage management (Network Appliance http://us.biz.yahoo.com/p/n/ntap.html).?
Abstract This paper presents an evaluation and critical review of Deidre Takeyama and Brian H. Kliener's 1998 article, which sheds light upon one aspect of discrimination that appears to encompass all other traits -employment discrimination. The paper discusses the soundness of the data reported, summarizes the content of the article and offers a personal evaluation/reaction to the material as well.
From the Paper "By categorizing employment discriminatory acts typology the reader would have been made aware that subtle and covert employment discrimination are very difficult to see, document and remedy. In fact, these two types often last a great deal longer than overt discriminatory acts. If one reviews additional publications in the area of employment discrimination very few research manuscripts are available dealing with subtle and covert employment discrimination."
Abstract This paper provides a basic introduction to ABC (Activity Based Costing) methods as a managerial accounting technique, a comparison to traditional based methods, benefits and disadvantages of ABC. The paper also includes an analysis of ABC methods as a TQM (Total Quality Management) component and provides a summary analysis of the system.
Table of Contents
Abstract
Introduction to Activity Based Accounting
Uses for ABC
Implementing ABC
Advantages of ABC Costing
Disadvantages of ABC Costing
ABC versus Traditional Accounting
The Concerns of Activity Based Management
Summary Analysis
References
From the Paper "Activity-Based Costing (ABC) arose in the 1980s from the increasing lack of relevance of traditional cost accounting methods. The traditional cost accounting methods were designed around 1870 - 1920 and in those days industry was labor intensive, there was no automation, the product variety was small and the overhead costs in companies were generally very low compared to today. However, from the 1960s - particularly 1980s - this changed rapidly. Activity Based Costing is based on a simple principle: activities consume resources and customers consume activities. Associating the labor and overhead expenses of the business with the activities that consume those resources provides valuable facts. ABC defines categories of activity in overhead departments, which on the one hand are recognizable to overhead department managers but, on the other hand, are driven by factors (cost drivers) which are characteristic of products and other cost objects. This allows a much higher proportion of total company cost to be allocated to products according to causation. Ultimately, ABC provides accounting data points that can be used to improve decision-making and identify cost improvement opportunities. The basic building blocks for ABC are activity accounting spreadsheets for each element of a business. The workload of each activity is measured resulting in a cost per output. "
Tags: comparison, flaws, component, cost, data, labor, y
Abstract This paper describes the business strategy of Space Data Corporation, beginning with a discussion on the initial business model and services offered by the company, a description of the product line strategy and a look at the economic model used to start the business. The paper continues with a discussion of the company's market potential, market segmentation and how the founders raised the capital to start their business. In addition, the paper touches upon the marketing strategy of the company and the technology issues the company faced.
Table of Contents:
The Nature of Entrepreneurial Management
Recognizing and Defining an Opportunity
Formulating a Business Concept
Product Line Strategy
Economic Model of the Business
Estimating Market Potential
Buyer Behavior and Market Segmentation
The Concepts of Objective, Strategies and Tactics/Types of Strategy
Resource Strategies and Leveraging
Finding Money and Raising Capital
Pro Forma Financial Statements
Valuation
Determining How Much Money is Needed
Deal Structure
Marketing Strategy and Tactics for a New Venture
Operations of the Business
Technology Issues within the Venture
Forms of Organization
Problems with Growth Strategies and Harvesting
From the Paper "Jerry first drew upon family capital, $500,000 total from family members. Board members were sought for their engineering and legal expertise to deal with government regulations regarding the technology, as well as familial loyalty and belief in the project concept, which cold keep legal and employee costs down. Overtures were made to Motorola, the international communications company that was enthused by the concept. The company continued to draw upon familial as well as corporate capital."
Tags: strategy, service-based model, segmentation financing, board members
Abstract In this article, the writer notes that modern technology has brought many wonderful innovations to our society, but it has also given rise to some new threats. The writer discusses that we are surrounded by identity-based information systems and dataveillance and argues that identity-based information systems pose serious risks to individual Canadians. While the writer concedes there are some advantages, the key problem is that they have become such an inextricable part of our economy and society that one cannot hope to adequately protect oneself against them - although there are some steps one can take to attempt to protect oneself. The writer argues that although there are some measures for protection in place, more are needed. This paper is written from a personal point of view. The writer also details the specific nature of the material discussed in each source.
From the Paper "Other institutions do not set out to use information to search for new customers, but they nevertheless collect information, often for security reasons. An example is that of the CIBC, one of Canada's biggest and most trusted banks. In 2004, the Privacy Commissioner had occasion to sternly criticize CIBC, after it was learned that the bank had been accidentally faxing confidential information to a scrap yard in West Virginia - for three years! At the time, the bank promised to tighten up security, so the Canadian public might have felt that their information is now safe with CIBC. But events of the past week have shown that this is not the case. CIBC announced on the 18th January 2007 that it had lost a file that contains personal details of almost half a million clients - those who held investment accounts with Talvest Mutual Funds, a fund under the management of CIBC Asset Management. This file went missing in December, but CIBC clients were only notified in mid-January - according to CIBC, this ignorance was in their best interests. Yet the misplaced information includes these clients' names, addresses, signatures, dates of birth, bank account numbers and social insurance numbers - more than enough to be used by other people to steal their identity, and then fraudulently enter into financial transactions."
Abstract The paper discusses how the many advances in data and text mining are already revolutionizing the librarian profession. The paper explores how the ability of data mining tools to extract, transfer and load (ETL) massive amounts of data at a single time, is changing how all tasks in an organization get completed.
Outline:
Executive Summary
Content Integration Is Key
Data Mining
i) Principles of Data Mining
ii) Data Mining Timeline
Data Mining Implications for Librarianship
Text Mining
i) Text Mining Timeline
ii) Data Mining versus Text Mining
iii) Mining Blogs: An Example of How Text Mining Works
Text Mining Implications for Librarianship
Conclusion
From the Paper "At the intersection of text mining, linguistic analysis, statistical analysis, and latent semantic indexing techniques (Wikipedia Latent Semantic Indexing 2006). is the future of text mining that has the power to discover and report trending in highly unstructured content. At the center of text-mining's' rapid growth is the increasing sophistication of Natural Language Processing (CRM Buyer 2005). IBM and their significant research efforts in natural language processing are well documented on their website, as are the efforts and investments Microsoft is making."
Tags: latent, semantic, indexing, clustering, hosted, applications, Island, Data, Attensity
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."
Abstract This paper explores data warehousing in terms of data mining with intelligent agents such as bots and ants and clarifies the ethical dilemma posed by the use of such data.
From the Paper " Data warehousing is no longer simply a storage system for data. Today's data warehousing involves innovative technological software, automated agents known as intelligent agents robots-or bots and ants. These agents ..."
Abstract This paper considers key factors regarding data warehousing. It looks at the goal of data warehousing and the differences of data warehousing and relational databases.
From the Paper "Data warehousing is particularly popular in environments which have complex data requirements and a broad spectrum of data types contained in its database. The goal of data warehousing is to take full advantage of the power of hardware to contain large quantities of data and use the databases to manipulate that data. Although not yet implemented across all computing environments data warehousing is becoming popular as hardware becomes more powerful and cost effective..."
Tags: distributed data warehousing systems, data warehouses
Abstract This paper discusses three articles on data collection and analysis tools and their applications. This includes data mining, data warehousing and software packages used in the collection. This paper also analyzes the needs of the business upon which the correct data collection and analysis tools are selected.
From the Paper "Business today has more and more need for external consultants to use data collection and analysis tools in order to make assessment of business operations and processes. Many of the methods used today are computer-based, including software that does much of the job but still requires an able human operator to make decisions and input the correct information. Various analysts have made assessments of these methods to see how they are used and how effective they may be. Such tools are also used for analyzing performance in education, for assessing public programs, and for other tasks requiring a decision as to the value of a program or process. Bielski (2001) discusses the use of CRM, or Customer Resource Management system, which is used to track customer purchases while providing access to customer information using the computer. "
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
