Activity 1 Part A) What event did you attend? ENTERPRISE INFORMATION MANAGEMENT An Overview of The Enterprise Data Warehouse and Business Intelligence Part B) When and where was it held? It was held at Sydney Mechanics School of Arts Level 1 280 Pitt Street on Wednesday 24th November 2010 between 6:30-7:30pm Activity 2 Part A) Write the details from the business card of the first person you met at this event. Ban Pradham He finished his masters degree at Macquire University and now he
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that protects the underlying attribute values of objects subjected to clustering analysis. In doing so‚ the privacy of individuals’ data would be protected. In this age of data mining‚ we felt that working on data privacy was of paramount importance. We worked in a group of 3 on this and my role specifically was to design and implement the ‘K-means’ algorithm that clusters the data and forms the basis for the data transformation. In addition to my thesis‚ I worked on a solo project which involved
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department store chain‚ which has many credit customers and wants to find out more information about these customers. A sample of 50 credit customers is selected with data collected on the following five variables. Location Rural Urban Suburban Income Size Year Credit Balance By analysis the data which is collected on above mentioned variable in StatCrunch (Minitab) we would identify the customer’s income level‚ credit balance and location that they live.
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3/20/2014 How eBay Uses Data and Analytics to Get Closer to Its (Massive) Customer Base | MIT Sloan Management Review How eBay Uses Data and Analytics to Get Closer to Its (Massive) Customer Base Big Idea: Data & Analytics • Interview • June 25‚ 2013 • Reading Time: 11 min Neel Sundaresan (eBay)‚ Interviewed by Renee Boucher Ferguson Online auction site eBay uses data about the behavior of its millions of customers to drive analytics at every level of the organization‚ and get closer
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Assignment one Introduction: Analysis of sports performance is of great importance to a higher performance sports coach. “Coaching is about enhancing an athlete(s) performance a principal means by which this achieved is through feedback however research as proven that human observation and memory are not reliable enough to provide the detailed information necessary to secure behavioural changes” (Franks and Miller 1986) P101. According to world renowned rugby union coach Graham Henry “A
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Essay 3 This essay provides an analysis of the variables‚ statistical tests and methods used in the assigned research paper. The level of significance and the strengths and limitations of the data collection process were also reviewed. This study had several variables. One major independent variable is the qualitative questionnaire that was verbally given. In this scenario the dependent variable would be the measurement of the data that was collected. The process of a cause-effect relationship
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CLUSTER ANALYSIS: ALGORITHMS AND ANALYSIS USING SAS BY: AHMED ALDAHHAN SUPERVISED BY: LECTURER JING XU BIRKBECK UNIVERSITY OF LONDON 2013/2014 ABSTRACT The scope of this paper is to provide an introduction to cluster analysis; by giving a general background for cluster analysis; and explaining the concept of cluster analysis and how the clustering algorithms work. A basic idea and the use of each clustering method will be described with its graphical features. Different clustering
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Analysis Tools Comparison: R Language‚ Matlab‚ esProc‚ SAS‚ SPSS‚ Excel‚ and SQL The interactive analysis is a circular analytics procedure comprising assumption‚ verification‚ and calibration by the analyst to achieve the fuzzy computation goal. For specifics and details‚ please refer to another article I composed: Interactive Analysis and Related Tools. Because there are so many tools for interactive analysis that not everyone can know all of them‚ I will only focus on and compare the most
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Quantitative Methods in Management. Sage Publications Principal Components Analysis Introduction Principal Components Analysis (PCA) attempts to analyse the structure in a data set in order to define uncorrelated components that capture the variation in the data. The identification of components is often desirable as it is usually easier to consider a relatively small number of unrelated components which have been derived from the data than a larger group of related variables. PCA is particularly useful
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Descriptive Data Analysis Descriptive Data Analysis for Nominal Variables: Gender and Local Political Party Activism Organize the Data into a Frequency Distribution Display the Data in a Graph Describe What Is Average or Typical of a Distribution Describe Variability Within a Distribution Describe the Relationship Between Two Variables Descriptive Data Analysis for Ordinal Variables: Continuing Our Research Example Organize the Data into a Frequency Distribution Display the Data in a
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