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    Cis 500: Cloud Computing

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    employ software updates and new applications quickly and more effectively. AWS services hundreds of thousands of customers in more than 190 countries‚ making their global infrastructure far more expansive than competitors; this allowed Ericsson to have data centers in various parts of the world. According to information provided in the case study‚ Ericsson chose AWS because they felt it was “the most integrated public cloud provider in the Rightscale Cloud Management Platform (Rightscale)”. Amazon

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    CIS 500 CASE STUDY 1

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    CIS 500 - CASE STUDY – The Big Data Challenges by CIS 500 Professor: October 28‚ 2013 CASE STUDY 1 Introduction In year 2010‚ Volvo Car Corporation separated from Ford and integrated the cloud infrastructure into its network. They needed to build up a new individual Information Technology infrastructure that could provide better business‚ increase communication capabilities and improve collaboration. This paper is going to explicate how Volvo Car Corporation transforms data into

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    Data Mining Soltions

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    contains only three base cells: (1) (a1‚ b2‚ c3‚ d4; ...‚ d9‚ d10)‚ (2) (a1‚ c2‚ b3‚ d4‚ ...‚ d9‚ d10)‚ and (3) (b1‚ c2‚ b3‚ d4‚ ...‚ d9‚ d10)‚ where a_i != b_i‚ b_i != c_i‚ etc. The measure of the cube is count. 1‚ How many nonempty cuboids will a full data cube contain? Answer: 210 = 1024 2‚ How many nonempty aggregate (i.e.‚ non-base) cells will a full cube contain? Answer: There will be 3 ∗ 210 − 6 ∗ 27 − 3 = 2301 nonempty aggregate cells in the full cube. The number of cells overlapping twice is 27

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    05 Subject :- CIS CASE STUDY 01 Ans 1:- The Technologies used by various companies for catching thieves were :- a) CCTV b) EAS There Limitations were :- a) They help us to catch the customers but does-not helps us to catch the employees within the Company. Ans 2:- Jaeger use the Data Mining applications which catch the thieving employees within the Company. Hence those employee which gave more discount in billing‚etc could be easily caught. With the help of Data Mining‚ the whole company

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    Learning and Data Mining Overview: Efficient asset allocation through statistical learning methods and comparison of methods for the creation of an index tracking ETF (Exchange traded fund) Datasets: The datasets are chosen from the website of the book “Statistics and Data Analysis for Financial Engineering” by David Ruppert. The book is mentioned as one of the references for this course. The two data sets chosen are 1. Stock_FX_Bond.csv 2. Stock_FX_Bond_2004_to_2006.csv The data includes

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    regression model to testing and validation dataset (output is in “LR_Output2”‚ “LR_Testscore2”‚ and “LR_ValidLiftChart2”). In testcore sheet‚ we can see the probability output we generated for each row from test data. Below shows the regression model and scoring summary. 3. a) the data of purchaser only is in “Purchasers_only” sheet b) Partition is shown in “Data_Partition2” sheet c) Multiple Linear regression output can be seen in “MLR_Output1”. Target variable is “spending”. We select every

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    International Journal of Computer Applications (0975 – 8887) Volume 41– No.5‚ March 2012 Data Mining Application in Enrollment Management: A Case Study Surjeet Kumar Yadav Saurabh pal Research scholar‚ Shri Venkateshwara University‚ J. P. Nagar‚ (U.P.) India Head‚ Dept. of MCA VBS Purvanchal University‚ Jaunpur‚ India ABSTRACT In the last two decades‚ number of Higher Education Institutions (HEI) grows rapidly in India. This causes a cut throat competition among these institutions

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    Data Mining: Introduction Lecture Notes for Chapter 1 Introduction to Data Mining by Tan‚ Steinbach‚ Kumar © Tan‚Steinbach‚ Kumar Introduction to Data Mining 4/18/2004 1 Why Mine Data? Commercial Viewpoint O Lots of data is being collected and warehoused – Web data‚ e-commerce – purchases at department/ grocery stores – Bank/Credit Card transactions O Computers have become cheaper and more powerful O Competitive Pressure is Strong – Provide better‚ customized services for an edge (e.g

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    DATA MINING IN HOMELAND SECURITY Abstract Data Mining is an analytical process that primarily involves searching through vast amounts of data to spot useful‚ but initially undiscovered‚ patterns. The data mining process typically involves three major steps—exploration‚ model building and validation and finally‚ deployment. Data mining is used in numerous applications‚ particularly business related endeavors such as market segmentation‚ customer churn‚ fraud detection‚ direct marketing‚ interactive

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    Data Mining Case Study

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    Company Information Applebee’s: Applebee’s International‚ Inc.‚ is an American company which develops‚ franchises‚ and operates the Applebee’s Neighborhood Grill and Bar restaurant chain. As of September 2011‚ there were 2‚010 restaurants operating system-wide in the United States‚ one U.S. territory and 14 other countries. The company is headquartered in Kansas City‚ Missouri after moving from Lenexa‚ Kansas in September 2011. The Applebee’s concept focuses on casual dining‚ with mainstream American

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