...Data Mining Nabeel Ahmed University of Northern Virginia Abstract ‘The vein of research data is almost always richer than it appears to be on the surface, but it can only be of value if mined.—Morris Rosenberg’ (AGOSTA, 2000) Recent years, Data Mining has become hot topic of enterprises. More and more companies intend to introduce data mining techniques. One report from the United States treats data mining as one of the ten favorable fields in the 21st century, of which by means shows its importance. Generally speaking, data mining are often applied in those fields, such as insurance and finance industries, retailing and direct marketing industries, communication industry, manufacturing industry and Medical service industry, etc. The data related to management decision making has been accumulating surprisingly quickly because of the improvement in high technology. As the byproduct of internet, e-commerce, e-banking, pos system, barcode scanner and intelligent robot, the acquirement of electronic data has already become cheap and existing everywhere. These data are normally stored in data warehouse and data marts to provide assistance for management decision-making. Data mining is a fast growing field, its main target is to develop some techniques to assist the managers in intelligent analyzing and utilizing mass data. Data mining was already being reported in successfully utilized in the aspects of credit rating, fraud detection, database marketing, customer relationship...
Words: 3916 - Pages: 16
...Data Mining Raymond Greer Michael Falat, PHD Info-System Decision Making March 10, 2014 Determine the benefits of data mining to the business when employing. 1a. Determine the benefits of data mining to the business when employing predictive analytics to the understanding of the behavior of customers. Predictive analytics is area of statistical analysis that deals with extracting information from data and using it to predict future trends and behavior. (Bland-Thomas, Karen 2013) It gathers information from a variety of different methods such as: statistics, modeling, machine learning and data mining which is made of current and past information that is used to form future predictions of marketing campaigns and the profit of an organization. Predictive analytics has a four step process to collecting information: 1. Establishing objective: Establish what information that you what to gather, develop a thesis with experts and the data that is required. 2. Collecting good and high quality information: Establish a prediction from consumer’s social media opinions such as: emails, tweets, Facebook posts etc. 3. Understanding consumer’s behavior and intent: Understanding consumer’s behavior and their intent by predicting with organizational wisdom. 4. Predict action: Predicting a consumer’s next purchase at the correct offer and time. Using this method offers many advantages for organizations that realize the value within the enterprise data. Strategically...
Words: 1922 - Pages: 8
...Data Mining By: Holly Gildea CIS 500 Dr. Janet Durgin June 09, 2013 Data Mining We learn that data mining is a method of evaluating data from different viewpoints and summarizing it into useful information. Such information can be beneficial and used to increase things like revenue, and cutting costs, and so on. There are four categories that we will look at and determine the benefits for in regards to data mining: predictive analytics to understand the behavior of customers, associations discovery in products sold to customers, web mining to discover business intelligence from web customers, and clustering to find related customer information. To understand the behavior of customers by the use predictive analytics we must first understand what predictive analytics is. “Predictive analytics is the process of dealing with a variety of data and applying various mathematical formulas to discover the best decision for a given situation” (ArticleSnatch, 2011). This gives any business a competitive edge and helps to remove the guess work out of the decision making process therefore helping to find the right solution in a shorter amount of time. In order to find the solution faster there are a seven simple steps that must be worked thru first: what is the problem for the company, searching for multiple data resources, take the patterns that are observed from that data, creating a model that contains the problem and the data, categorize the data and find important...
Words: 1843 - Pages: 8
...[pic] Data Mining Assignment 4 [pic] “Data mining software is one of a number of analytical tools for analyzing data (Data Mining, para. 1).” We will be learning about the competitive advantage, reliability of such tool, and privacy concerns towards consumers. Data mining tool is used by majority of companies to increase revenue, and build on the relationship with current consumers. Let’s explore the world of data mining technology in the following selection. “Data mining is primarily used today by companies with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these companies to determine relationships among "internal" factors such as price, product positioning, or staff skills, and "external" factors such as economic indicators, competition, and customer demographics. And, it enables them to determine the impact on sales, customer satisfaction, and corporate profits. Finally, it enables them to "drill down" into summary information to view detail transactional data (Data Mining, para. 7).” Data mining is implemented online to promote business ideas, products, and other ways to market them. Data mining is used in political websites, when you go to some sites they take your information then, they began to send you things to promote the Republicans and Democrats message. This is how your voice counts. “Companies have used powerful computers to sift through volumes of supermarket scanner data and analyze market research...
Words: 1183 - Pages: 5
...Data Mining Data Mining THE BUSINESS SCHOOL, KASHMIR UNIVERSITY 5/18/2014 THE BUSINESS SCHOOL, KASHMIR UNIVERSITY 5/18/2014 Umer Rashid Roll No 55 Umer Rashid Roll No 55 Abstract: Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. CRM: In today’s competitive scenario in corporate world, “Customer Retention” strategy in Customer Relationship Management (CRM) is an increasingly pressed issue. Data mining techniques play a vital role in better CRM. This paper attempts to bring a new perspective by focusing the issue of data mining Applications, opportunities and challenges in CRM. It covers the topic such as customer retention, customer services, risk assessment, fraud detection and some of the data mining tools which are widely used in CRM. Supply Chain Management (SCM) environments are often dynamic markets providing a plethora of Information, either complete or incomplete. It is, therefore, evident that such environments demand...
Words: 2588 - Pages: 11
...BUSINESS INTELLIGENCE DATA MINING Business intelligence is a computerized technique used is searching, storing and analyzing useful business information (http://en.wikipedia.org/wiki/Business_intelligence). Business intelligence is an increasing strategy employed by many modern ventures, in the attempt to providing quick access to information and helps the business in making appropriate decisions. Holistic information on ones business environment is an important tool, since it does not only shows your past trend, but also prepares the firm for the future improvements. This sets a challenge in establishing the methods to source for the information, and how to use this information to improve a business position . Data mining is the sourcing of any hidden and predictive business information from a relevant database. It involves a thorough analysis of data gained from various sources, manipulating it into useful tool - a tool that leads to raising business revenue, saving on the running costs or both (http://en.wikipedia.org/wiki/Data_mining). Data mining tool incorporates analytical tools that helps build a useful predictive relationship. Data mining tools helps get answers as it scrutinizes data from different perspective to a precision, than any expert could do. Interplay of data mining process with software and hardware utilities is a big step in data analysis. The integration of artificial intelligence and databases heightens the data-mining goal as the information is translated...
Words: 1904 - Pages: 8
...Running Head: DATA MINING Assignment 4: Data Mining Submitted by: Submitted to: Course: Introduction Data Mining is also called as Knowledge Discovery in Databases (KDD). It is a powerful technology which has great potential in helping companies to focus on the most important information they have in their data base. Due to the increased use of technologies, interest in data mining has increased speedily. Data mining can be used to predict future behavior rather than focus on past events. This is done by focusing on existing information that may be stored in their data warehouse or information warehouse. Companies are now utilizing data mining techniques to assess their database for trends, relationships, and outcomes to improve their overall operations and discover new ways that may permit them to improve their customer services. Data mining provides multiple benefits to government, businesses, society as well as individual persons (Data Mining, 2011). Benefits of data mining to the businesses when employing Advantages of data mining from business point of view is that large sizes of apparently pointless information have been filtered into important and valuable business information to the company, which could be stored in data warehouses. While in the past, the responsibility was on marketing utilities and services, products, the center of attention is now on customers- their choices, preferences, dislikes and likes, and possibly data mining is one of the most important tools...
Words: 1302 - Pages: 6
...Chapter 12 Business Intelligence and Decision Support Systems Goals of the Chapter The primary objective of this chapter is to recognize the importance of data, the management issues that relate to it, and its life cycle. Other objectives include relating data management to multimedia and document management, explaining the concept of data warehousing, data mining, analytical processing, and knowledge discovery management. An Overview Section 12.1 – The Need for Business Intelligence – The section serves as an overview of Business Intelligence and its use in business. It discusses the problems associated with disparate data stores where data are not integrated into a single reporting system. The section discusses the technologies involved in Business Intelligence and the vendors involved. It also talks about predictive analytics, alerts and decision support. Section 12.2 – BI Architecture, Reporting and Performance Management – This section discusses the modes of data extraction and integration into a standardized, usable and trustworthy one. It also discusses the different types of reporting systems available to organizations, data mining, query and analysis. The section provides an insight into Business Performance Management (BPM) as a way for business managers to know if their organizations are achieving their strategic goals Section 12.3 – Data, Text and Web Mining and BI Search – This section discusses data mining technology, tools, and techniques. Information types...
Words: 5712 - Pages: 23
...Data Mining/Data Warehousing Matthew P Bartman Strayer University Ibrahim Elhag CIS 111– Intro to Relational Database Management June 9, 2013 Data Mining/Data Warehousing When it comes to technology especially in terms of storing data there are two ways that it can be done and that is through data mining and data warehousing. With each type of storage there are trends and benefits. In terms of data warehousing there are 5 key benefits one of them being that it enhance business intelligence. What this means is that business processes can be applied directly instead of things having to be done with limited information or on gut instinct. Another benefit of data warehousing is that it can also save time meaning that if a decision has to be made the data can be retrieved quickly instead of having to find data from multiple sources. Not only does data warehousing enhance business intelligence and save time but it can also enchance data quality and consistency.This is accomplished by converting all data into one common format and will make it consistent with all departments which ensures accuracy with the data as well. While these key benefits another one is that it can provide historical intelligence which means that analayze different time periods and trends to make future predictions. One other key benefit is that it provides a great return on investment. The reason being that a data warehouse generates more revenue...
Words: 2018 - Pages: 9
...com/locate/techsoc Data mining techniques for customer relationship management Chris Rygielski a, Jyun-Cheng Wang b, David C. Yen a,∗ a Department of DSC & MIS, Miami University, Oxford, OH, USA b Department of Information Management, National Chung-Cheng University, Taiwan, ROC Abstract Advancements in technology have made relationship marketing a reality in recent years. Technologies such as data warehousing, data mining, and campaign management software have made customer relationship management a new area where firms can gain a competitive advantage. Particularly through data mining—the extraction of hidden predictive information from large databases—organizations can identify valuable customers, predict future behaviors, and enable firms to make proactive, knowledge-driven decisions. The automated, future-ori- ented analyses made possible by data mining move beyond the analyses of past events typically provided by history-oriented tools such as decision support systems. Data mining tools answer business questions that in the past were too time-consuming to pursue. Yet, it is the answers to these questions make customer relationship management possible. Various techniques exist among data mining software, each with their own advantages and challenges for different types of applications. A particular dichotomy exists between neural networks and chi-square automated interaction detection (CHAID). While differing approaches abound in the realm of data mining, the...
Words: 8031 - Pages: 33
...Data Mining Professor Clifton Howell CIS500-Information Systems Decision Making March 7, 2014 Benefits of data mining to the businesses One of the benefits to data mining is the ability to utilize information that you have stored to predict the possibilities of consumer’s actions and needs to make better business decisions. We implement a business intelligence that will produce a predictive score for those consumers to determine these possibilities. Predictive analytics is the business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model which has, in turn, been trained over your data, learning from the experience of your organization. (Impact, 2014) The usefulness of predictive scoring is obvious. However, with no predictive model and no means to score your consumer, the possibility of gaining a competitive edge and revenue is also predictable. To discover consumer buying patterns from a transaction database, mining association rules are used to make better business decisions. However because users may only be interested in certain information from this database and do not want to invest a lot of time in searching for what they need, association discovery will assist in limiting the data to which only the end user needs. Association discovery will utilize algorithms to lessen the quantity of groupings of item sets or sequences in each customer...
Words: 1318 - Pages: 6
...Original Contributions Data Mining Applications in Healthcare Hian Chye Koh and Gerald Tan A B S T R A C T Data mining has been used intensively and extensively by many organizations. In healthcare, data mining is becoming increasingly popular, if not increasingly essential. Data mining applications can greatly benefit all parties involved in the healthcare industry. For example, data mining can help healthcare insurers detect fraud and abuse, healthcare organizations make customer relationship management decisions, physicians identify effective treatments and best practices, and patients receive better and more affordable healthcare services. The huge amounts of data generated by healthcare transactions are too complex and voluminous to be processed and analyzed by traditional methods. Data mining provides the methodology and technology to transform these mounds of data into useful information for decision making. This article explores data mining applications in healthcare. In particular, it discusses data mining and its applications within healthcare in major areas such as the evaluation of treatment effectiveness, management of healthcare, customer relationship management, and the detection of fraud and abuse. It also gives an illustrative example of a healthcare data mining application involving the identification of risk factors associated with the onset of diabetes. Finally, the article highlights the limitations of data mining and discusses some future directions....
Words: 5507 - Pages: 23
...Data Mining Introduction to Management Information System 04-73-213 Section 5 Professor Mao March 22, 2011 Group 5: Carol DeBruyn, Jason Rekker, Matt Smith, Mike St. Denis Odette School of Business – The University of Windsor Table of Contents Table of Contents ……………………………………………………………...…….………….. ii Introduction ……………………………………………………………………………………… 1 Data Mining ……………………………………………………………………...……………… 1 Text Mining ……………………………………………………………………...……………… 4 Conclusion ………………………...…………………………………………………………….. 7 References ………………………………………………..……………………………………… 9 Introduction Everyday millions of transactions occur at thousands of businesses. Each transaction provides valuable data to these businesses. This valuable data is then stored in data warehouses and data marts for later reference. This stored data represents a large asset that until the advent of data mining had been largely unexploited. As companies attempt to gain a competitive advantage over each other, new data mining techniques have been developed. The most recent revolution in data mining has resulted in text mining. Prior to text mining, companies could only focus on leveraging their numerical data. Now companies are beginning to benefit from the textual data stored in data warehouses as well. Data Mining Data mining, which is also known as data discovery or knowledge discovery is the procedure that gathers, analyzes and places into perspective useful information. This facilitates the analysis of data from...
Words: 2331 - Pages: 10
...Benefits of data mining to the businesses: Data Mining. Assignment 4 Mustafa Abdullah Strayer University Dr. Jodine Burchell 08/30/2012 Data Mining is a useful tool in the business world today. Data Mining is a process that uses statistical information to gather useful information knowledge from data warehouses. Data Mining can be used for many reasons when gathering information. Businesses that use it are finance, retail and banks for the purpose of finding information on a company or individual. Most business use data mining to predict sales, credit card fraud and to find out what makes the patient ill. HR departments use data mining to predict the value of the employee. Robert (2006)” The eventual goal is to project how much workers will produce over their careers”(para6). This tactic helps companies predict employees who will stay longer in the company as time goes by. The information is then stored into their database to help in the hiring process. “ Robert(2006)”Companies will be able to carry out cost-benefit studies on recruiting, training, and employee retention (along with its counterpart, layoffs)”.Base on this information companies are tired of playing the guessing game but data mining gives them a more accurate look. All the data gathered such as videos email, social media helps the HR understand the person and gives the business clues. Data Mining gives HR the ability to understand a person and search for the best job candidates through social media...
Words: 316 - Pages: 2
...Introduction 2 Assumptions 3 Data Availability 3 Overnight processing window 3 Business sponsor 4 Source system knowledge 4 Significance 5 Data warehouse 6 ETL: (Extract, Transform, Load) 6 Data Mining 6 Data Mining Techniques 7 Data Warehousing 8 Data Mining 8 Technology in Health Care 9 Diseases Analysis 9 Treatment strategies 9 Healthcare Resource Management 10 Customer Relationship Management 10 Recommended Solution 11 Corporate Solution 11 Technological Solution 11 Justification and Conclusion 12 References 14 Health Authority Data (Appendix A) 16 Data Warehousing Implementation (Appendix B) 19 Data Mining Implementation (Appendix B) 22 Technological Scenarios in Health Authorities (Appendix C) 26 Technology Tools 27 Data Management Technology Introduction The amount of information offered to us is literally astonishing, and the worthiness of data as an organizational asset is widely acknowledged. Nonetheless the failure to manage this enormous amount of data, and to swiftly acquire the information that is relevant to any particular question, as the volume of information rises, demonstrates to be a distraction and a liability, rather than an asset. This paradox energies the need for increasingly powerful and flexible data management systems. To achieve efficiency and a great level of productivity out of large and complex datasets, operators need have tools that streamline the tasks of managing the data and extracting valuable...
Words: 8284 - Pages: 34
