Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific
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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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face with scary image. From this I came with an idea for my game with few adaptions‚ in this case the adaptions are the red balls and the ‘replay a level’ screen. Technical research For technical research I used the school computers‚ internet and PowerPoint. Design Ideas Ideas that I considered were: * Core colour for all the slides * Ball to kill of players * How the game is structured * Time limit * Extra lives Final Design Ideas That design that I ended up with is:
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Rishi Tripathy AP US History 8/24/13 Summer Reading Assignment Chapter 3: Compare and contrast the government‚ religion‚ geography‚ and economy of the three English colonial regions. Be sure to consider the role of race‚ gender‚ and ethnicity. English colonies in America were‚ for the most part‚ successful and fruitful‚ albeit for starkly different reasons. The three regions of New England‚ the Carolinas and the Chesapeake Bay had different ways of earning their ways‚ which translated
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University of Illinois April 9‚ 2014 127 years old and still growing Organic growth top and bottom line Reinventing ourselves with new segments and disciplined acquisitions 2 A 127-year History of Quality Affordable Healthcare Products® Unico Holdings 1887 1921 2005 2006 2007 2008 2010 2011 2012 2013 2014 Introduction of “private label” 3 Growth & Achievements Since 2009* Focused on Operational Excellence / Five Pillars
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MGW2351 International business Unit Guide Summer semester‚ 2014 Copyright © Monash University 2014. All rights reserved. Except as provided in the Copyright Act 1968‚ this work may not be reproduced in any form without the written permission of the host Faculty and School/Department. The information contained in this unit guide is correct at time of publication. The University has the right to change any of the elements contained in this document at any time. Last updated: 25 Nov 2014 Table of
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University Of Ibadan Faculty of Social Science Department of Economics Course of 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
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Lush Presentation – Data/ Sources Country Selection – 1) India – Chosen country 2) Turkey 3) China Country Selection- We originally had 3 different countries which we choose from and we managed to do a process of elimination‚ we did this by looking at different parts of the country and taking into account all the factors which will have an impact on Lush if those chose to expand their business to that particular country
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Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed
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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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