...Data Mining 0. Abstract With the development of different fields, artificial intelligence, machine learning, statistic, database, pattern recognition and neurocomputing they merge to a newly technology, the data mining. The ultimate goal of data mining is to obtain knowledge from the large database. It helps to discover previously unknown patterns, most of the time it is followed by deeper manual evaluation to explain and correlate the results to establish a new knowledge. It is often practically used by government, bank, insurance company and medical researcher. A general basic idea of data mining would be introduced. In this article, they are divided into four types, predictive modeling, database segmentation, link analysis and deviation detection. A brief introduction will explain the variation among them. For the next part, current privacy, ethical as well as technical issue regarding data mining will be discussed. Besides, the future development trends, especially concept of the developing sport data mining is written. Last but not the least different views on data mining including the good side, the drawback and our views are integrated into the paragraph. 1. Introduction This century, is the age of digital world. We are no longer able to live without the computing technology. Due to information explosion, we are having difficulty to obtain knowledge from large amount of unorganized data. One of the solutions, Knowledge Discovery in Database (KDD) is introduced...
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...Data mining is an iterative process of selecting, exploring and modeling large amounts of data to identify meaningful, logical patterns and relationships among key variables. Data mining is used to uncover trends, predict future events and assess the merits of various courses of action. When employing, predictive analytics and data mining can make marketing more efficient. There are many techniques and methods, including business intelligence data collection. Predictive analytics is using business intelligence data for forecasting and modeling. It is a way to use predictive analysis data to predict future patterns. It is used widely in the insurance, medical and credit industries. Assessment of credit, and assignment of a credit score is probably the most widely known use of predictive analytics. Using events of the past, managers are able to estimate the likelihood of future events. Data mining aids predictive analysis by providing a record of the past that can be analyzed and used to predict which customers are most likely to renew, purchase, or purchase related products and services. Business intelligence data mining is important to your marketing campaigns. Proper data mining algorithms and predictive modeling can narrow your target audience and allow you to tailor your ads to each online customer as he or she navigates your site. Your marketing team will have the opportunity to develop multiple advertisements based on the past clicks of your visitors. Predictive...
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...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...
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...Data Mining Teresa M. Tidwell Dr. Sergey Samoilenko Information Systems for Decision Making September 2, 2012 Data Mining The use of data mining by companies assists them with identifying information and knowledge from databases and data warehouses that would be beneficial for the company. The information is often buried in databases, records, and files. With the use of tools such as queries and algorithms, companies can access data, analyze it, and use it to increase their profit. The benefits of using data mining, its reliability, and privacy concerns will be discussed. Benefits of Data Mining 1. Predictive Analytics: This type of analysis uses the customer’s data to make a specific model for the business. Existing information is used such as a customer’s recent purchases and their income, to create a prediction of future purchases and how much or what type of item would be purchased. The more variables used the more likely that the prediction will be correct. Such variables include the customer ranking, based on the number of and most recent purchases and the average profit made per customer purchase. Without data made available through web access and purchases by the customer, predictive analysis would be difficult to perform. The company, therefore, would not be able to plan nor predict how well they are performing. 2. Associations Discovery: This part of data mining helps the company to discover the “relationships hidden in larger data sets” (Pang-Ning...
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...The increasing use of data mining by corporations and advertisers obviously creates apprehension from the perspective of the individual consumer due to privacy, security and the potential use of inaccurate information. The idea that there are data warehouses that contain customers’ personal information can be rather frightening. However, the use of data mining by these organizations can also lead to numerous benefits for consumers they otherwise would not have realized. Besides the obvious benefit of guiding consumers to products or services they’d be more interested in purchasing, the use of data mining by companies has also benefitted individuals’ health and financial safety. Not long after the use of data mining came into prominence the use of data mining consumer information vs. consumer privacy became a major issue in early 1998 after CVS and Giant entered into an agreement with Elensys, a Massachusetts direct marketing company, to send reminders to customers who had not renewed their prescriptions. However, neither CVS nor Giant explained how the program would work or received their customers' permission to transfer their prescription records to a third party (Pyatt Jr.). Giant and CVS’s rationale for entering into this agreement was “to develop a positive program to benefit consumers, many of whom don't take their medication properly,” (Pyatt Jr.). Even though their primary intention was good, Giant and CVS were not transparent about their agreement with Elensys...
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...Data Mining Objectives: Highlight the characteristics of Data mining Operations, Techniques and Tools. A Brief Overview Online Analytical Processing (OLAP): OLAP is the dynamic synthesis, analysis, and consolidation of large volumns of multi-dimensional data. Multi-dimensional OLAP support common analyst operations, such as: ▪ Considation – aggregate of data, e.g. roll-ups from branches to regions. ▪ Drill-down – showing details, just the reverse of considation. ▪ Slicing and dicing – pivoting. Looking at the data from different viewpoints. E.g. X, Y, Z axis as salesman, Nth quarter and products, or region, Nth quarter and products. A Brief Overview Data Mining: Construct an advanced architecture for storing information in a multi-dimension data warehouse is just the first step to evolve from traditional DBMS. To realize the value of a data warehouse, it is necessary to extract the knowledge hidden within the warehouse. Unlike OLAP, which reveal patterns that are known in advance, Data Mining uses the machine learning techniques to find hidden relationships within data. So Data Mining is to ▪ Analyse data, ▪ Use software techniques ▪ Finding hidden and unexpected patterns and relationships in sets of data. Examples of Data Mining Applications: ▪ Identifying potential credit card customer groups ▪ Identifying buying patterns of customers. ▪ Predicting trends of market...
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...DATA MINING Generally, data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Data mining software is one of a number of tools for analyzing data. It allows users to analyze data from many different dimensions or angels, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding patterns among dozens of fields in large databases that are similar to one another. Data is any facts, numbers, or text that can be processed by a computer so in general it makes it easier for a company or business to see what the majority of customers want at a time. It’s almost like a survey that we don’t realize we are taking. I think it really can benefit consumers because we can walk into a place of business and see what we want on the shelves because it is in demand. Even better, the things we don’t want to purchase are not there because there is no demand for it. It gives us the choice to be heard and have a say in making decisions on things that impact us most. Information can be converted into knowledge about historical patterns and future trends. For example, summary information on retail supermarket sales can be analyzed in light of promotional efforts to provide knowledge of consumer buying behavior. Thus, a manufacturer or retailer could determine which items are most susceptible to promotional efforts. I don’t think data...
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...DATA MINING FOR INTELIIGENCE LED POLICING The paper concentrates on use of data mining techniques in police domain using associative memory being the main technique. The author talks of constructing the data being easier and thus giving effective decision making. The author does mention making the process as simple as possible since there are not enough technically sound people into databases. The process involves a step procedural method. Further the author does explain the advantages of this system in police environment. The author mentions use of data mining activities by Dutch forces and how it makes the work easier to predict and analyze the scenario. The author talks about the tool and name given to it as Data detective. This tool involved a chunk of data stored in data warehouse. There has been a continuous development in the tool used here throughout the years making it more efficient than before. The data mining tool automatically predicts the trend and the lays down all the statistical report. This tool makes it easier for the police to pin out criminals and their trends easily. The process raises a challenge so that a predictive modeling can be developed better than before. The author talks about understanding the links and then predicting is important. The author also mentions that this involves pattern matching which is achieved by data mining. The tool also helps in automatic prediction of criminal nature matches a profile and this leads to be quite...
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...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...
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...Data Mining 6/3/12 CIS 500 Data Mining is the process of analyzing data from different perspectives and summarizing it into useful information. This information can be used to increase revenue, cut costs or both. Data mining software is a major analytical tool used for analyzing data. It allows the user to analyze data from many different angles, categorize the data and summarizing the relationships. In a nut shell data mining is used mostly for the process of finding correlations or patterns among fields in very large databases. What ultimately can data mining do for a company? A lot. Data mining is primarily used by companies with strong customer focus in retail or financial. It allows companies to determine relationships among factors such as price, product placement, and staff skill set. There are external factors that data mining can use as well such as location, economic indicators, and competition of other companies. With the use of data mining a retailer can look at point of sale records of a customer purchases to send promotions to certain areas based on purchases made. An example of this is Blockbuster looking at movie rentals to send customers updates regarding new movies depending on their previous rent list. Another example would be American express suggesting products to card holders depending on monthly purchases histories. Data Mining consists of 5 major elements: • Extract, transform, and load transaction data onto the data...
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...1. Define data mining. Why are there many different names and definitions for data mining? Data mining is the process through which previously unknown patterns in data were discovered. Another definition would be “a process that uses statistical, mathematical, artificial intelligence, and machine learning techniques to extract and identify useful information and subsequent knowledge from large databases.” This includes most types of automated data analysis. A third definition: Data mining is the process of finding mathematical patterns from (usually) large sets of data; these can be rules, affinities, correlations, trends, or prediction models. Data mining has many definitions because it’s been stretched beyond those limits by some software vendors to include most forms of data analysis in order to increase sales using the popularity of data mining. What recent factors have increased the popularity of data mining? Following are some of most pronounced reasons: * More intense competition at the global scale driven by customers’ ever-changing needs and wants in an increasingly saturated marketplace. * General recognition of the untapped value hidden in large data sources. * Consolidation and integration of database records, which enables a single view of customers, vendors, transactions, etc. * Consolidation of databases and other data repositories into a single location in the form of a data warehouse. * The exponential increase...
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...Data Mining Information Systems for Decision Making 10 December 2013 Abstract Data mining the next big thing in technology, if used properly it can give businesses the advance knowledge of when they are going to lose customers or make them happy. There are many benefits of data mining and it can be accomplished in different ways. The problem with data mining is that it is only as reliable as the data going in and the way it is handled. There are also privacy concerns with data mining. Keywords: data mining, benefits, privacy concerns Data Mining Benefits of Data Mining for a Business Data mining can be explained as the process of a business collecting data on their customers or potential customers to increase customer business. A business will collect data on their customers or potential customers and use that data to give them coupons, promote sells, and analyze buying and selling trends. Data mining can benefit the customer as well as the business. Data mining can be used in the retail industry, the finance industry, and the healthcare industry. Any industry can benefit from data mining but those are the top three (Turban & Volonino, 2011). Data mining is a way for large businesses to get to know their customers. The information gathered from data mining can let a large company learn what their customers want and how they want it. It can also benefit large companies get to know their employees, the company can learn how to satisfy their...
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...Data Mining Prepared by: Kirsten Sullivan Strayer University CIS 500 Dr. Baab September 9, 2012 Data mining is a concept that companies use to gain new customers or clients in an effort to make their business and profits grow. The ability to use data mining can result in the accrual of new customers by taking the new information and advertising to customers who are either not currently utilizing the business's product or also in winning additional customers that may be purchasing from the competitor. Generally, data are any “facts, numbers, or text that can be processed by a computer.”1 Today, organizations are accumulating vast and growing amounts of data in different formats and different databases. This includes operational or transactional data such as, sales, cost, inventory, payroll, and accounting. Data mining also known as “knowledge discovery”, is the process of analyzing data from different perspectives and summarizing it into useful information- information that can then be used to increase revenue, cuts costs, and continue the goals outlined for the company. Data mining consists of five major elements: “Extract, transform, and load transaction data onto the data warehouse system, store and manage the data in a multidimensional database system, provide data access to business analysts and information technology professionals, analyze the data by application software, present the data in a useful format, such as a graph or table.”2...
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...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...
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...[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...
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