is a necessity for a businesses trying to maximize its profits. A new‚ and important‚ tool in gaining this knowledge is Data Mining. Data Mining is a set of automated procedures used to find previously unknown patterns and relationships in data. These patterns and relationships‚ once extracted‚ can be used to make valid predictions about the behavior of the customer. Data Mining is generally used for four main tasks: (1) to improve the process of making new customers and retaining customers;
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that moulds data into a structure which is similar to the underlying system of database management model. Systems of database management are categorized into three main types: hierarchical‚ relational‚ and network. Database design is a process to organize data into a form which matches the underlying data model of the database management system. There are three major types of database management systems: network‚ hierarchical‚ and relational. In the network database management systems‚ which include
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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 Processing Data Processing is the term generally used to describe what was done by large mainframe computers from the late 1940’s until the early 1980’s (and which continues to be done in most large organizations to a greater or lesser extent even today): large volumes of raw transaction data fed into programs that update a master file‚ with fixed-format reports written to paper. Number System A numeral system (or system of numeration) is a writing system for expressing numbers‚ that is
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DATA ORGANIZATION‚ PRESENTATION AND ANALYSIS Research Methods 1 Data Organization and Presentation To make interpretation and analysis of gathered data easier‚ data should be organized and presented properly. The usual methods used by researchers are textual‚ tables‚ graphs and charts. 1.1 Textual Data can be presented in the form of texts‚ phrases or paragraphs. It involves enumerating important characteristics‚ emphasizing significant figures and identifying important features of
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Data Anomalies Normalization is the process of splitting relations into well-structured relations that allow users to inset‚ delete‚ and update tuples without introducing database inconsistencies. Without normalization many problems can occur when trying to load an integrated conceptual model into the DBMS. These problems arise from relations that are generated directly from user views are called anomalies. There are three types of anomalies: update‚ deletion and insertion anomalies. An update anomaly
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Learning project On the Indraprastha Cold Storage Limited INDEX S.N. Topic Page No. 1. Introduction 4 2. Issues with IPCSL 6 3. IPCSL pricing strategy 7 3. Non Price Strategies for long term growth 10 4. Economic value to customer of improved services. 12 5. How IPCSL can communicate values to customers 14 6. Conclusion 15 7. References 16 Introduction
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Glycogen Storage Disease type III is an autosomal recessive disorder that is caused by the deficiency of the glycogen debrancher enzyme. This deficiency causes there to be a mutation on exon three and it causes abnormally structured glycogen to be present in the body. This disease can be diagnosed by multiple tolerance tests and it also can be diagnosed by analyzing the muscle tissues. This disease causes problems in the liver and in the muscles. The tolerance tests are used to test for liver diseases
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Chapter 1 Exercises 1. What is data mining? In your answer‚ address the following: Data mining refers to the process or method that extracts or \mines" interesting knowledge or patterns from large amounts of data. (a) Is it another hype? Data mining is not another hype. Instead‚ the 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. Thus‚ data mining can be viewed as the result of
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EE2410: Data Structures Cheng-Wen Wu Spring 2000 cww@ee.nthu.edu.tw http://larc.ee.nthu.edu.tw/˜cww/n/241 Class Hours: W5W6R6 (Rm 208‚ EECS Bldg) Requirements The prerequites for the course are EE 2310 & EE 2320‚ i.e.‚ Computer Programming (I) & (II). I assume that you have been familiar with the C programming language. Knowing at least one of C++ and Java is recommended. Course Contents 1. Introduction to algorithms [W.5‚S.2] 2. Recursion [W.7‚S.14] 3. Elementary data structures: stacks‚ queues
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