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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The Difference Between Data Centers and Computer Rooms By Peter Sacco Experts for Your Always Available Data Center White Paper #1 EXECUTIVE SUMMARY The differences between a data center and a computer room are often misunderstood. Furthermore‚ the terms used to describe the location where companies provide a secure‚ power protected‚ and environmentally controlled space are often used inappropriately. This paper provides a basis for understanding the differences between these locations
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ingredients of a sustainable supply chain strategy Apply a generic‚ iterative approach to develop your sustainable supply chain strategy Apply a balanced scorecard to implement your sustainable supply chain strategy 2.1 Introduction: The Starting Point Long-term trends pose challenges for supply chain managers and make increasing requirements on the strategic management expertise of today’s companies. These trends include ongoing globalisation and the increasing intensity of competition‚ the
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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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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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research because they allow the researchers to analyze empirical data needed to interpret the findings and draw conclusions based on the results of the research. According to Portney and Watkins (2009)‚ all studies require a description of subjects and responses that are obtained through measuring central tendency‚ so all studies use descriptive statistics to present an appropriate use of statistical tests and the validity of data interpretation. Although descriptive statistics do not allow general
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Interpreting your data is a process that involves answering a series of questions about the research. We suggest the following steps: 1) Review and interpret the data "in-house" to develop preliminary findings‚ conclusions‚ and recommendations. 2) Review the data and your interpretation of it with an advisory group or technical committee. This group should involve local‚ regional‚ and state resource people who are familiar with monitoring and with your product. They can verify‚ add to‚ or
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Data Gathering ➢ used to discover business information details to define the information structure ➢ helps to establish the priorities of the information needs ➢ further leads to opportunities to highlight key issues which may cross functional boundaries or may touch on policies or the organization itself ➢ highlighting systems or enhancements that can quickly satisfy cross-functional information needs ➢ a complicated task especially in a large and complex system ➢ must
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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 Alonso‚ ETH Zurich‚ Switzerland Prof. Bettina
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1 Secondary data analysis: an introduction All data are the consequence of one person asking questions of someone else. (Jacob 1984: 43) This chapter introduces the field of secondary data analysis. It begins by considering what it is that we mean by secondary data analysis‚ before describing the type of data that might lend itself to secondary analysis and the ways in which the approach has developed as a research tool in social and educational research. The second part of the chapter considers
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