Name :- Dhaval Ruparel Batch :- SMBA – 13 Roll No :- 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
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Questionnaire Dear Participants‚ I will be very thankful to you for this cooperation. The topic of this questionnaire is Role of Packaging in Consumer Buying Behavior. This questionnaire is for the research purpose. Its results will be used for analysis in Master Thesis. Please provide Information with confidence. Your information will not be disclosed. Personal Information Name : Gender : Age : Profession : Education : E-Mail : Contact No : Rating of Questions Strongly Disagree
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COM5407 Financial Communication & Promotion Individual Assignment As the product manager‚ I propose to employ the data mining techniques‚ as an important implementation of our Customer Relationship Management (CRM) strategy‚ to better understand the clients of our third party products and increase our profitability. Our bank has various sorts of third party products ranging from mutual funds‚ insurance products to bonds. Commission is earned on selling other companies ’ products. Although
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CXC SOCIAL STUDIES PROJECT SCHOOL BASED ASSESSEMENT (S.B.A) (YEAR 2013) NAME OF CANDIDATE: SCHOOL: CHRIST CHURCH FOUNDATION SCHOOL CENTRE #: CANDIDATE #: TEACHER: Mr. Harrison TITLE: An examination of the attitude of high school students towards homosexuality among the youth in Barbados. Table of Contents Page ACKNOWLEDGEMENT INTRODUCTION As a teenager growing up in my homeland Barbados‚ I have noticed that over the past years the
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CUSTOMER SATISFACTION SURVEY OF NEPAL SBI BANK Your responses are anonymous and confidential. 1. Gender 1. Male [ ] 2. Female [ ] 2. Age 1. 30 years and below [ ] 2. 31-40 years [ ] 3. 41-50 years [ ] 4. Over 50years [ ] 3. What is your primary occupation? 1. Business Man [
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Question 1. Define what is thin‚ fat/thick client. Thin-client is a technology whereby it refers to a computer that has multi-tier client server architecture which the end user (client) do not use any hard disk and the programs run and display via browser. The program is actual execute from main server and not from desktop pc. The client which operates as terminal needs to continuously communicate with the server. Thick or Fat client is a technology whereby it also refers to a computer with multi-tier
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Questions for an exit interview • Tell me about how you’ve come to decide to leave? • What is your main reason for leaving? • What are the other reasons for your leaving? • Why is this important‚ or so significant for you? • Within the (particular reason to leave) what was it that concerned you particularly? • What could have been done early on to prevent the situation developing/provide a basis for you to stay with us? • How would you have preferred the situation(s)
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A Comparative Study between Intellectual Quotient and Emotional Quotient of Employees as Perceived by the Human Resource Manager of Selected Private Companies in Ortigas‚ Pasig City PART I. Personal Information Directions: Put a check (√) to your corresponding answer. Only one (1) answer per question is allowed. Name (Optional): ________________________________________________________ Age: _________ Sex: _____ Male Civil Status: ______ Single _____ Female ______ Married
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Qualitative Data‚ Descriptive Research Design: Survey & Observation‚ Causal Research Design: Experimentation‚ Measurement & Scaling: Fundamental & Comparative Scaling‚ Measurement & Scaling: Non-Comparative Scaling Techniques‚ Questionnaire Form & Design‚ zxcvbnmqrtyuiopasdfghjklzxcvbnmqwertyuiopasdfghjklzxcvbnmqwe rtyuiopasdfghjklzxcvbnmqwertyuiopasdfghjklzxcvbnmqwertyuiopa sdfghjklzxcvbnmqwertyuiopasdfghjklzxcvbnmqwertyuiopasdfghjkl zxcvbnmrtyuiopasdfghjklzxcvbnmqwertyuiopasdfghjklzxcvbnmqwer
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Building Data Mining Applications for CRM Introduction This overview provides a description of some of the most common data mining algorithms in use today. We have broken the discussion into two sections‚ each with a specific theme: • Classical Techniques: Statistics‚ Neighborhoods and Clustering • Next Generation Techniques: Trees‚ Networks and Rules Each section will describe a number of data mining algorithms at a high level‚ focusing on the "big picture" so that the reader will
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