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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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    New Analysis Part 2 Essay: Should You Make Or Should You Buy? Outsourcing Hotel Operations Recently When an entrepreneur wants to join the hotel industry‚ he can search for a property company for a building for lease to operate his hotel rather than to build it by his capital. Nowadays‚ there are so many hotel chain do not own the buildings which contribute the hotels‚ such as Choice Hotels International company‚ which own 11 hotel brands: Comfort Inn‚ Comfort Suites‚

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    Data Preprocessing

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    IT433 Data Warehousing and Data MiningData 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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    Birmingham City University 10/6/2010 Submitted to: Graham Cooper From: Hassan Shafqat (S10524689) Birmingham City University 10/6/2010 1st Case Study 1st Case Study Kellogg is the world’s leading cereal producer and out of the total value £1.1 billion per year of the UK cereals market Kellogg has a market share of 42%. This is 21st century and being very fast people want such a lifestyle in which the food they eat can equally contributes to their health. Kellogg’s aim is exactly the

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    Consumer Data

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    Handling Consumer Data Introduction When I visit my local Caltex Woolworths petrol station on “cheap fuel Wednesday” to cash in the 8c per litre credit that my Wife earned the previous Friday buying the groceries with our “Everyday Rewards” card‚ I did not‚ until researching this report‚ have any clue as to the contribution I was making to a database of frightening proportions and possibilities… nor that‚ when I also “decide” to pick up the on-sale‚ strategically-placed 600mL choc-milk‚ I am

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    Big Data

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    Big DataData Mining and Business Intelligence Techniques 2 What is Data? • Data is information in a form suitable for use with a computer. • There are two types of data ▫ Structured ▫ Unstructured • The total volume of data is growing 59% every year. • The number of files grow at 88% every year. 3 What is Big Data? Exa Analytics on Big Data at Rest Up to 10‚000 Times larger Peta Data Scale Giga Data at Rest Tera Data Scale Mega Traditional Data Warehouse

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    Big Data

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    Systems Coursework Part 1: Big Data Student ID: 080010830 March 16‚ 2012 Word Count: 3887 Abstract Big data is one of the most vibrant topics among multiple industries‚ thus in this paper we have covered examples as well as current research that is being conducted in the field. This was done based on real applications that have to deal with big data on a daily basis together with a clear focus on their achievements and challenges. The results are very convincing that big data is a critical subject that

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    Big Data

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    Turning data into information © Copyright IBM Corporation 2007 Course materials may not be reproduced in whole or in part without the prior written permission of IBM. 4.0.3 Unit objectives After completing this unit‚ you should be able to: Explain how Business and Data is correlated Discuss the concept of turning data into information Describe the relationships between DW‚ BI‚ and Data Insight Identify the components of a DW architecture Summarize the Insight requirements and goals of

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    Big Data

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    Networks Volvo utilized data mining in an effort to discover the unknown valuable relationships in the data collected and to assist in making early predictive information. It created a network of sensors and CPUs that were embedded throughout the cars and from which data was captured. Data was also captured from customer relationship systems (CRM)‚ dealership systems‚ product development and design systems and from the production floors in their factories. The terabytes of data collected was streamed

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    Paper ID – IC 554 The Actions and Future of Web Mining Ms. Preety Khatri Mr. Sanjay Pachauri Mr. Ritesh Singhal (Pursuing PhD‚ MCA‚ (Pursuing PhD‚ M.Tech (Pursuing PhD‚ M.Phil‚ M.Phil) MBA(IT)‚ MCSE‚ MSc.) M.Sc.‚ MIT) Lecturer(IT)‚ Coordinator PGDM Associate Professor‚ HOD-IT Associate Professor‚HOD-

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