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    Big Data

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    Big Data Myisha Coleman July 22‚ 2012 Big Data Dr. Dani Babb Big Data The Volvo Car Corporation was founded in 1927. Since that time the company prides itself upon leading its competitors in safety and engineering

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    Customer Data

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    CUSTOMER DATA In the term of customer data‚ technology now day give a big role to evaluate the concepts by the overall to moving ownership of the customer when they are away from the individual departments and different it at the enterprise level. In the customer relationship management concept‚ individual that in the each department has responsible for the customer. The success factor for Customer Relationship Management (CRM) is by deploying technology that provides various levels of data access

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    Data Structures

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    Data Structures and Algorithms DSA Annotated Reference with Examples Granville Barne Luca Del Tongo Data Structures and Algorithms: Annotated Reference with Examples First Edition Copyright c Granville Barnett‚ and Luca Del Tongo 2008. This book is made exclusively available from DotNetSlackers (http://dotnetslackers.com/) the place for .NET articles‚ and news from some of the leading minds in the software industry. Contents 1 Introduction 1.1 What this book is‚ and what

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    Data Mining

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    Data Mining Information Systems for Decision Making 10 December 2013 Abstract Data mining the next big thing in technology‚ if used properly it can give businesses the advance knowledge of when they are going to lose customers or make them happy. There are many benefits of data mining and it can be accomplished in different ways. The problem with data mining is that it is only as reliable as the data going in and the way it is handled. There are also privacy concerns with data mining

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    Design and Data

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    There are many key differences that are important to understand between data oriented and process oriented approaches to designing a new system. The system focus of the data views and process views are entirely different. The process view focuses on what the systems supposed to do and when‚ while the data view has a focus on what the system needs to operate. Another noteworthy difference that distinguishes the two views is the design stability. The design stability of a process view is a more limited

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    Big Data

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    billion bytes of data in digital form be it on social media‚ blogs‚ purchase transaction record‚ purchasing pattern of middle class families‚ amount of waste generated in a city‚ no. of road accidents on a particular highways‚ data generated by meteorological department etc. This huge size of data generated is known as big data. Generally managers use data to arrive at decision. Marketers use data analytics to determine customer preferences and their purchasing pattern. Big data has tremendous potential

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    DATA MANAGEMENT

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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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    data mining

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    Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed

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    data mining

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    Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific

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    Secondary data

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    Secondary data refers to the data which an investigator does not collect himself for his purpose rather he obtains them from some other source‚ agency or office. In other words‚ this data has already been collected by some other source and an investigator makes use of it for his purpose. Secondary data is different from primary data on the basis of the sources of their collection. The difference between the two is relative - data which is primary at one place become secondary at another place.

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