business intelligence‚ data warehouse‚ data mining‚ text and web mining‚ and knowledge management. Justify and synthesis your answers/viewpoints with examples (e.g. eBay case) and findings from literature/articles. To understand the relationships between these terms‚ definition of each term should be illustrated. Firstly‚ business intelligence (BI) in most resource has been defined as a broad term that combines many tools and technologies‚ used to extract useful meaning of enterprise data in order to help
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Topic 1: The Data Mining Process: Data mining is the process of analyzing data from different perceptions and summarizing it into useful evidence that can be used to increase revenue‚ cut 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. Association‚ Clustering‚ predictions and sequential patterns‚ decision trees and classification
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CHAPTER 7 Revenue and Collection Cycle LEARNING OBJECTIVES Review Checkpoints Exercises‚ Problems‚ and Simulations 1. Discuss inherent risks related to the revenue and collection cycle with a focus on improper revenue recognition. 1‚ 2‚ 3 59 2. Describe the revenue and collection cycle‚ including typical source documents and controls. 4‚ 5‚ 6‚ 7‚ 8 54‚ 55‚ 61‚ 63‚ 64‚ 66 3. Give examples of tests of controls over customer credit approval‚ delivery‚ and
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IT433 Data Warehousing and Data Mining — Data Preprocessing — 1 Data Preprocessing • Why preprocess the data? • Descriptive data summarization • Data cleaning • Data integration and transformation • Data reduction • Discretization and concept hierarchy generation • Summary 2 Why Data Preprocessing? • Data in the real world is dirty – incomplete: lacking attribute values‚ lacking certain attributes of interest‚ or containing only aggregate data • e.g.‚ occupation=“ ”
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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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1 Secondary data analysis: an introduction All data are the consequence of one person asking questions of someone else. (Jacob 1984: 43) This chapter introduces the field of secondary data analysis. It begins by considering what it is that we mean by secondary data analysis‚ before describing the type of data that might lend itself to secondary analysis and the ways in which the approach has developed as a research tool in social and educational research. The second part of the chapter considers
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7 ANALYZING THE AUTHOR’S PURPOSE AND TECHNIQUE T he writer’s overall purpose determines the techniques he or she uses. The writer’s reason for writing a particular article or book may be manipulative‚ as in propaganda or advertising‚ or may be more straightforward‚ as in informative writing. In either case‚ understanding the writer’s underlying purpose will help you interpret the context of the writing. It will also help you see why writers make the decisions they do—from the largest
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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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Maceration Techniques and Methods The interest in maceration‚ in the anthropological perspective‚ began in the 19th century. Over the following century the largest ambitious endeavor was the maceration of thousands of individuals‚ this collection is known as the Hamann-Todd Collection (Dawnie 11). Maceration according to the Merriam-Webster Dictionary is‚ “to cause to become soft or separated into constituent elements by or as if by steeping in fluid”. Maceration is a form of controlled putrefaction
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TYPES OF DATA AND COMPONENTS OF DATA STRUCTURES Data types 1. Primitive: is a data type provided by a programming language as a basic building block 2. Composite: is any data type which can be constructed in a program using its programming language’s primitive data types and other composite types 3. Abstract: is a mathematical model for a certain class of data structures that have similar behavior; or for certain data types of one or more programming languages that have similar semantics
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