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    1. Question: A characteristic or quality describing an entity is called a(n): Your Answer: Field Tuple Key field Attribute ( pp. 210 ) CORRECT Points Received: 2 of 2 Comments: 2. Question: Duplicate data in multiple data files is: Your Answer: Data redundancy ( p. 211 ) CORRECT Data multiplication Data independence Data backups Points

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    Data Comms

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    Internet bandwidth requirements kept challenging traditional‚ software-based packet processing architectures. The perceived complexity of programming routing functions in silicon‚ led to formation of several startups determined to find new ways to process IP and MPLS packets entirely in hardware and blur boundaries between routing and switching. One of them‚ Juniper Networks‚ shipped their first product in 1999 and by 2000 chipped away about 30% from Cisco SP Market share. Cisco answered the challenge

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    Secondary Data

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    Q) What are Secondary Data? Secondary Data Secondary data is information gathered for purposes other than the completion of a research project. Data previously collected by someone else‚ possibly for some other purpose that can be used later for making decisions if found suitable for the purpose‚ other than the original one. Secondary data can be acquired from the internal records of the organization‚ their departments‚ subsidiaries or sister organizations and also from external sources‚ such

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    Data Description

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    Chapter 3 Data Description 3-1 Measures of Central Tendency ( page 3-3) Measures found using data values from the entire population are called: parameter Measures found using data values from samples are called: statistic A parameter is a characteristic or measure obtained using data values from a specific population. A statistic is a characteristic or measure obtained using data values from a specific sample. The Measures of Central Tendency are: • The Mean • The

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    Data Services

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    Data Services Vodafone’s Data Services are tailored to make you stay competitive even as your needs change. We provide simplified network solutions to improve your productivity and also offer customized solutions that save organizations from having to deal with multiple providers. We offer entry-level products using ADSL technology to high-end solutions delivered through a mix of ATM‚ Frame Relay or IP/VPN over MPLS-established technologies that alleviate pressure on your IT resources and give you

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    Data Analytics

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    MIS2502: Exam 1 Study Guide The exam will be a combination of short-answer and multiple-choice questions. It is a closed-book‚ closed-notes exam. You will not be able to use a computer during the exam. The following is a list of items that you should review in preparation for the exam. Note that not every item on this list may be on the exam‚ and there may be items on the exam not on this list. The Things You Can Do With Data/The Information Architecture of an Organization What is the difference

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    Data Science

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    Services E20-007 Data Science and Big Data Analytics Exam Exam Description Overview This exam focuses on the practice of data analytics‚ the role of the Data Scientist‚ the main phases of the Data Analytics Lifecycle‚ analyzing and exploring data with R‚ statistics for model building and evaluation‚ the theory and methods of advanced analytics and statistical modeling‚ the technology and tools that can be used for advanced analytics‚ operationalizing an analytics project‚ and data visualization techniques

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    Data Mining

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    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; (2) to reduce fraud; (3) to identify

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    Data Mining

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    Data Mining Abdullah Alshawdhabi Coleman University Simply stated data mining refers to extracting or mining knowledge from large amounts of it. The term is actually a misnomer. Remember that the mining of gold from rocks or sand is referred to as gold mining rather than rock or sand mining. Thus‚ data mining should have been more appropriately named “knowledge mining from data‚” which is unfortunately somewhat long. Knowledge mining‚ a shorter term‚ may not

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    Data Analysis

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    Research methods: Data analysis G Qualitative analysis of data Recording experiences and meanings Distinctions between quantitative and qualitative studies Reason and Rowan’s views Reicher and Potter’s St Paul’s riot study McAdams’ definition of psychobiography Weiskrantz’s study of DB Jourard’s cross-cultural studies Cumberbatch’s TV advertising study A bulimia sufferer’s diary G Interpretations of interviews‚ case studies‚ and observations Some of the problems involved in drawing

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