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
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Data Mining Weekly Assignment 6: LIFT; CRM; AFFINITY POSITIONING; CROSS-SELLING AND ITS ETHICAL CONCERNS. What is meant by the term “lift”? The term “lift” describes the improved performance of an exact or specific amount of effort on a modeled sampling‚ as opposed to a random sampling (Spang‚ 2010). In other words‚ if you are able to market via a model to say‚ a given number of random customers (e.g. 1000)‚ and we expect that 50 of them would be successful‚ then a model that can generate 75
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The Ocean Ranger The Ocean Ranger was an offshore exploration oil drilling platform that sank in Canadian waters 315 kilometres southeast from St. John’s Newfoundland‚ on the Grand Banks of Newfoundland on February 15‚ 1982‚ with 84 crewmembers onboard. The Ocean Ranger was the largest semi-submersible‚ offshore exploration‚ oil drilling platform of the day. Built in 1976 by Japan’s Mitsubishi Heavy Industries‚ it operated off the coasts of Alaska‚ New Jersey‚ Ireland‚ and in November 1980 moved
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The importance of mining is definitely significant to Canada. Mining‚ is an important industry‚ and Canadians are very advanced in their mining technology‚ but during the mining process‚ there is certain level of pollution produced. The Canadian government and the mining companies have very good plans and controls toward this problem‚ while ensuring the smooth running of the industries‚ and also helping to create strong economy and employment. The world of today could not exist without mineral products
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Lovely professional university CASE STUDY OF DATA MINING Summitted by Jatin Sharma Roll no -32. Reg. no 10802192 A case study in Data Warehousing and Data mining Using the SAS System. Data Warehouses The drop in price of data storage has given companies willing to make the investment a tremendous resource:
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Data Mining: What is Data Mining? Overview 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
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Funding Space Exploration ENG122: English Composition II Funding Space Exploration There are many issues that occur within our planet such as the so called upcoming war with North Korea‚ animal extinction‚ economy issues‚ lack of jobs‚ etc. that needs attention and a well thought out plan so it can be dealt with. The subject area that I will be discussing is based on Science‚ Health and Environmental Issues. The main topic I will be discussing and debating on the issue
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Data Mining Abdullah Alshawdhabi Coleman University Simply stated data mining refers to extracting or mining knowledge from large amounts of it. The term is actually a misnomer. Remember that the mining of gold from rocks or sand is referred to as gold mining rather than rock or sand mining. Thus‚ data mining should have been more appropriately named “knowledge mining from data‚” which is unfortunately somewhat long. Knowledge mining‚ a shorter term‚ may not
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4 Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity
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Chapter 1 Exercises 1. What is data mining? In your answer‚ address the following: Data mining refers to the process or method that extracts or \mines" interesting knowledge or patterns from large amounts of data. (a) Is it another hype? Data mining is not another hype. Instead‚ the need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. Thus‚ data mining can be viewed as the result of the
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