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    Data Mining

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    Data Mining DeMarcus Montgomery Dr. Janet Durgin CIS 500 June 9‚ 2013 Determine the benefits of data mining to the businesses when employing 1. Predictive analytics to understand the behavior of customers Predictive analytics is 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

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    Data Mining

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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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    Big Data

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    Trang Vuong Big Data and Its Potentials Data exists everywhere nowadays. It flows to every area of the economy and plays an important role in the decision-making process. Indeed‚ “businesses‚ industries‚ governments‚ universities‚ scientists‚ consumers‚ and nonprofits are generating data at unprecedented levels and at an incredible pace” to ensure the accuracy and reliability of their data-driven decisions (Gordon-Murnane 30). Especially when technology and economy are growing at an unbelievable

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    Data Mining

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    Data Mining Melody McIntosh Dr. Janet Durgin Information Systems for Decision Making December 8‚ 2013 Introduction Data mining‚ or knowledge discovery‚ is the computer-assisted process of digging through and analyzing enormous sets of data and then extracting the meaning of the data. Data mining tools predict behaviors and future trends‚ allowing businesses to make proactive‚ knowledge- driven decisions Although data mining is still in its infancy

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    Data Structure

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    Module 815 Data Structures Using C M. Campbell © 1993 Deakin University Module 815 Data Structures Using C Aim After working through this module you should be able to create and use new and complex data types within C programs. Learning objectives After working through this module you should be able to: 1. Manipulate character strings in C programs. 2. Declare and manipulate single and multi-dimensional arrays of the C data types. 3. Create‚ manipulate and manage C pointers

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    Data Comm

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    DATA COMMUNICATION (Basics of data communication‚ OSI layers.) K.K.DHUPAR SDE (NP-II) ALTTC ALTTC/NP/KKD/Data Communication 1 Data Communications History • 1838: Samuel Morse & Alfred Veil Invent Morse Code Telegraph System • 1876: Alexander Graham Bell invented Telephone • 1910:Howard Krum developed Start/Stop Synchronisation ALTTC/NP/KKD/Data Communication 2 History of Computing • 1930: Development of ASCII Transmission Code • 1945: Allied Governments develop the First Large Computer

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    Data Analysis

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    calculator. Please write all the answers with a BALL-POINT PEN or an INK PEN. If you have any questions during the exam‚ please raise your hand. GOOD LUCK!!! I am sure you guys will do great. Multiple Choice Identify the letter of the choice that best completes the statement or answers the question and write it in the space given next to the question number. Each multiple choice question is worth 1 point. ____ ____ ____ ____ ____ 1. In a questionnaire‚ respondents are asked to mark

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    Data Mining

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    Data mining Data mining is simply filtering through large amounts of raw data for useful information that gives businesses a competitive edge. This information is made up of meaningful patterns and trends that are already in the data but were previously unseen. The most popular tool used when mining is artificial intelligence (AI). AI technologies try to work the way the human brain works‚ by making intelligent guesses‚ learning by example‚ and using deductive reasoning. Some of the more popular

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    Big Data

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    Big Data Management: Possibilities and Challenges The term big data describes the volumes of data generated by an enterprise‚ including Web-browsing trails‚ point-of-sale data‚ ATM records‚ and other customer information generated within an organization (Levine‚ 2013). These data sets can be so large and complex that they become difficult to process using traditional database management tools and data processing applications. Big data creates numerous exciting possibilities for organizations‚

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    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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