4V of Big Data? Imagine all the information you alone generate each time you swipe your credit card‚ post to social media‚ drive your car‚ leave a voicemail‚ or visit a doctor. Now try to imagine your data combined with the data of all humans‚ corporations‚ and organizations in the world! From healthcare to social media‚ from business to the auto industry‚ humans are now creating more data than ever before. volume‚ velocity‚ variety‚ and veracity. Volume: Scale of Data Big data is big. It’s
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Internet in mid-to-late 1990s quickly changed the telecom landscape. As the Internet Protocol (IP) became widely adopted‚ the importance of multi-protocol routing declined. Nevertheless‚ Cisco managed to catch the Internet wave‚ with products ranging from modem access shelves (AS5200) to core GSR routers that quickly became vital to Internet service providers and by 1998 gave Cisco de facto monopoly in this critical segment.Meanwhile‚ the growth of Internet bandwidth requirements kept challenging traditional
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Data Collection Method/Research Design-Capstone Project The research design utilized will be a guide for data collection. In this instance‚ the project outline will aid in selecting the types of data to collect‚ analyze and review. Additionally‚ the outline will assist in keeping the research focused‚ and lessen the chances of becoming overwhelmed by the sheer volume of data that is available for review. In collecting data for this Capstone Project‚ secondary data review and analysis is the
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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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for67757_fm.fm Page i Saturday‚ January 7‚ 2006 12:00 AM DATA COMMUNICATIONS AND NETWORKING for67757_fm.fm Page ii Saturday‚ January 7‚ 2006 12:00 AM McGraw-Hill Forouzan Networking Series Titles by Behrouz A. Forouzan: Data Communications and Networking TCP/IP Protocol Suite Local Area Networks Business Data Communications for67757_fm.fm Page iii Saturday‚ January 7‚ 2006 12:00 AM DATA COMMUNICATIONS AND NETWORKING Fourth Edition Behrouz A. Forouzan DeAnza College with
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PRINCIPLES OF DATA QUALITY Arthur D. Chapman1 Although most data gathering disciples treat error as an embarrassing issue to be expunged‚ the error inherent in [spatial] data deserves closer attention and public understanding …because error provides a critical component in judging fitness for use. (Chrisman 1991). Australian Biodiversity Information Services PO Box 7491‚ Toowoomba South‚ Qld‚ Australia email: papers.digit@gbif.org 1 © 2005‚ Global Biodiversity Information Facility Material
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its simplest terms‚ the translation of data into a secret code. In order to read an encrypted file‚ the receiver of the file must obtain a secret key that will enable him to decrypt the file. A deeper look into cryptography‚ cryptanalysis‚ and the Data Encryption Standard (DES) will provide a better understanding of data encryption. Cryptographic Methods There are two standard methods of cryptography‚ asymmetric encryption and symmetric encryption. Data that is in its original form (unscrambled)
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Data Mining: What is Data Mining? Overview Generally‚ data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue‚ cuts 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
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Turnage‚ Bonebright‚ Buhman‚ Flowers (1996) showed that untrained participants can listen to shapes. That is‚ they used data sonification – musical representation of two dimensional space‚ with pitch as the vertical dimension and time as the horizontal dimension – to present participants the visual and auditory representation of waveforms. In two conditions‚ they showed the participants could match one visual presentation to one of two auditory representations‚ or match one auditory presentation
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and cross talk on a cabling medium are factors that prevent the accuracy of transmitted data to be intact. For these reasons different encoding methods exist. An example is when 2 wires are used to transmit music data to a speaker Digital signals don’t always have to be carried over to the receiving end by electricity‚ light can also be used for digital communication. Fibre Optics use light to transmit data through optical fibre within the cable. The strength of the light ray can also be a determining
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