Data transmission‚ digital transmission‚ or digital communications is the physical transfer of data (a digital bit stream) over a point-to-point or point-to-multipoint communication channel. Examples of such channels are copper wires‚ optical fibres‚ wireless communication channels‚ and storage media. The data are represented as an electromagnetic signal‚ such as an electrical voltage‚ radiowave‚ microwave‚ or infrared signal. Data representation can be divided into two categories: Digital
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What is Data Communications? Next Topic | TOC The distance over which data moves within a computer may vary from a few thousandths of an inch‚ as is the case within a single IC chip‚ to as much as several feet along the backplane of the main circuit board. Over such small distances‚ digital data may be transmitted as direct‚ two-level electrical signals over simple copper conductors. Except for the fastest computers‚ circuit designers are not very concerned about the shape of the conductor or
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Data Mining Project – Dogs Race Prediction Motivation Gambling is very popular in the Republic of Ireland‚ weather is online or not‚ more people are joining gambling communities formed all over the Island of Ireland. The majority of these communities are involved in horse races related gambling and other sports‚ but there is a significant amount of people dedicated to dogs races. This is a multimillion Euro industry developed on-line and live or face to face. Objective There are many websites
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Outline Introduction Distributed DBMS Architecture Distributed Database Design Distributed Query Processing Distributed Transaction Management Data Replication Consistency criteria Update propagation protocols Parallel Database Systems Data Integration Systems Web Search/Querying Peer-to-Peer Data Management Data Stream Management Distributed & Parallel DBMS M. Tamer Özsu Page 6.1 Acknowledgements Many of these slides are from notes prepared by Prof. Gustavo
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CHAPTER 12 ROUTING IN SWITCHED NETWORKS A NSWERS TO Q UESTIONS 12.1 The average load expected over the course of the busiest hour of use during the course of a day. 12.2 The tradeoff is between efficiency and resilience. 12.3 A static routing strategy does not adapt to changing conditions on the network but uses a fixed strategy developed ahead of time. With alternate routing‚ there are a number of alternate routes between source and destination and a dynamic choice of routes is
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it for any other purpose. DATE: 06/10/2013 Introduction: In data mining it is said that “success or failure often depends not only on how well you are able to collect data but also on how well you are able to convert them into knowledge that will help you better manage your business (Wilson‚ 2001‚ p. 26).” Tourism and hospitality industry generates massive amount of data. In each and every transaction there is set of data generated. In tourism and hospitality‚ knowing your customer is very
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Activity 1 Reasons why organisations need to collect HR Data. It is important for organisations to collect and retain HR data as this will be key for strategic and HR planning. It will also help to have all the information necessary to make informed decisions‚ for the formulation and implementation of employment policies and procedures‚ to monitor fair and consistent treatment of staff‚ to contribute to National Statistics and to comply with statutory requirements. The key organisational
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1. Data mart definition A data mart is the access layer of the data warehouse environment that is used to get data out to the users. The data mart is a subset of the data warehouse that is usually oriented to a specific business line or team. Data marts are small slices of the data warehouse. Whereas data warehouses have an enterprise-wide depth‚ the information in data marts pertains to a single department. In some deployments‚ each department or business unit is considered the owner of its data
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IT433 Data Warehousing and Data Mining — Data Preprocessing — 1 Data Preprocessing • Why preprocess the data? • Descriptive data summarization • Data cleaning • Data integration and transformation • Data reduction • Discretization and concept hierarchy generation • Summary 2 Why Data Preprocessing? • Data in the real world is dirty – incomplete: lacking attribute values‚ lacking certain attributes of interest‚ or containing only aggregate data • e.g.‚ occupation=“ ”
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an era of big data‚ this data-driven world has the potential to improve the efficiencies of enterprises and improve the quality of our lives; however‚ there are a number of challenges that must be addressed to allow us to exploit the full potential of big data. This paper focuses on challenges faced by online retailers when making use of big data. With the provided examples of online retailers Amazon and eBay‚ this paper addressed the key challenges of big data analytics including data capture and
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