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    Data

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    Next Generation Mobile Analytical Instruments Palm Nuclear Magnetic Resonance System (PNMR) University Research & Entrepreneurship Symposium April 1‚ 2010 Dr. Marcus Semones WaveGuide Corporation WaveGuide is an early stage mobile analytical instrument company building a suite of next generation handheld (i) infrared and (ii) nuclear magnetic resonance spectrometers for portable use in multiple untapped markets. WaveGuide’s business model: •Acquire exclusive worldwide licensing for existing

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    Case analysis-Harrington Collection Problem identification In 2008‚ Harrington Collection‚ a large manufacturer and retailer of U.S. high-end women’s apparel‚ was facing opportunities and challenges whether to launch of active-wear products to meet the market and customers’ needs. But according to the macroeconomic environment‚ the target market‚ competitors and its own financial condition‚ Harrington needed to take careful consideration and then make the best decision for their own

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    Teleoxy Collection Case

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    1. Using expected value‚ is it economically better to make or buy the component? According to the contextual investigation‚ Teloxy designing buys the little part expected to fabricate the item is $60 esteem for each piece‚ and the building group changed the assessments to $72 appreciation for each section. Teloxy needs to make 10‚000 item pieces (Ciel‚ S.C. 2011). Considering the proposal from the building group and their market estimation procedures‚ the Teloxy’s item adds up to expenses can

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    TYPES OF DATA AND COMPONENTS OF DATA STRUCTURES Data types 1. Primitive: is a data type provided by a programming language as a basic building block 2. Composite: is any data type which can be constructed in a program using its programming language’s primitive data types and other composite types 3. Abstract: is a mathematical model for a certain class of data structures that have similar behavior; or for certain data types of one or more programming languages that have similar semantics

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    Data Warehousing and Data mining December‚ 9 2013 Data Mining and Data Warehousing Companies and organizations all over the world are blasting on the scene with data mining and data warehousing trying to keep an extreme competitive leg up on the competition. Always trying to improve the competiveness and the improvement of the business process is a key factor in expanding and strategically maintaining a higher standard for the most cost effective means in any

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    Big Data

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    Patrick Cunningham ITM220-J November 8‚ 2013 Big Data Big Data‚ an inspirational novel about the collection and processing of massive amounts of data was eye-opening and encouraging. This collection of data over a long period of time has been processed and used towards many different aspects throughout the world. Dilemmas such as tracking the H1N1 virus‚ to buying the most inexpensive plane tickets‚ all the way to predicting dangerous manholes explosions have all been processed and tabulated

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    Hr Data

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    develop a sound understanding of the knowledge‚ skills and behaviour required of a professional practitioner‚ whether their role is generalist in nature or specialist‚ for example L&D. It will enable learners to develop a personal development plan‚ following a self-assessment of learning and development needs‚ that meets their personal and professional requirements. This unit is suitable for persons who: • are aspiring to‚ or embarking on‚ a career in HR/L&D • are working in the

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    What is Data

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    study: MBA Course Title: Marketing Research Course code: MBA 763 Assignment: Secondary Data Mat Number: 74168 Name: Abiona Timothy Olufemi What is Data Data is a collection of facts‚ such as numbers‚ words‚ measurements‚ observations or even just descriptions of things. 1.Information in raw or unorganized form (such as alphabets‚ numbers‚ or symbols) that refer to‚ or represent‚ conditions‚ ideas‚ or objects. Data is limitless and present everywhere in the universe. See also information and knowledge

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    Data Quality

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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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    significantly feasible. Background of the Study Transit fare collection technology has evolved from the manual – based systems in used before 1970 to automated systems with computer – based hardware and software. These major advancements in fare collection have been made possible through advances in the design of fare media‚ the use of micro-processors and software in fare collection equipment‚ and the development of sophisticated control and data communications systems. A more-recent innovation has been

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