Information Systems Management Research Project ON Data Warehousing and Data Mining Submitted in Partial fulfilment of requirement of award of MBA degree of GGSIPU‚ New Delhi Submitted By: Swati Singhal (12015603911) Saba Afghan (11415603911) 2011-2013
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Data Mining: Introduction Lecture Notes for Chapter 1 Introduction to Data Mining by Tan‚ Steinbach‚ Kumar © Tan‚Steinbach‚ Kumar Introduction to Data Mining 4/18/2004 1 Why Mine Data? Commercial Viewpoint O Lots of data is being collected and warehoused – Web data‚ e-commerce – purchases at department/ grocery stores – Bank/Credit Card transactions O Computers have become cheaper and more powerful O Competitive Pressure is Strong – Provide better‚ customized services for an edge (e.g
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help businesses achieve competitive advantage‚ can the data be used to model underlying business processes‚ and can we gain insights from the data to help improve business processes? These are the goals of Business Intelligence (BI) systems‚ and Data Mining is the set of embeddable (in BI systems) analytic methods that provide the capabilities to explore‚ summarize‚ and model the data. Before applying these methods to data‚ the data has to be typically organized into history repositories‚ known as data
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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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A Paper on Data preprocessing and Measures of Similarities and Dissimilarities and Data Mining Applications DEEPAK KUMAR D R M.SC IN COMPUTER SCIENCE 3RD SEMESTER‚ DAVANGERE UNIVERSITY deepakrdevang@gmail.com Abstract: This topic is mainly used by a number of data mining techniques‚ such as clustering‚ nearest neighbor classification‚ and anomaly detection. And it can also include the data mining applications.In this paper we have focused a variety of techniques‚ approaches and different areas
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Title: “Data Mining: The Mushroom Database” Author: Hemendra Pal Singh* In this review “Data Mining: The Mushroom Database” is focuses in the study of database or datasets of a mushroom. The purpose of the research is to broaden the preceding researches by administer new data sets of stylometry‚ keystroke capture‚ and mouse movement data through Weka. Weka stands for Waikato environment for knowledge analysis‚ and it is a popular suite of machine learning software written in Java‚ developed at
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SMALL-SCALE MINING (Lives at risk in the Philippine Gold Mines) INTRODUCTION Gold is the number one mineral produced by the Philippines in value terms. Although total local production was low relative to world production‚ it ranked 2nd to Africa in gold production per unit land area in 1988 and ranked 29th as top gold producer in 2002(Israel and Asirot 2002). In the year 2002–2007‚ the Philippines’ gold production increased by 8.2%. This contributed an average of 2% gross domestic product (GDP)
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1. Porters 5 forces Analysis: 1.1 Buyer power: The buyers for mining industry usually have medium to high power. There are two elements that could affect the buyer’s power. One is buyer’s level of negotiation; the other is buyer’s price sensitivity. In our case‚ the two companies are producing coal and uranium. These two products are mainly used for producing electricity. Buyers for these natural resources must have large quantity of demand‚ and also they usually have government behind
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MANAGEMENT 8 ANATOMY OF A FAILED KNOWLEDGE MANAGEMENT INITIATIVE: LESSONS FROM PHARMACORP’S EXPERIENCES 8 BENEFITS OF KNOWLEDGE MANAGEMENT 9 DATA MINING 10 FACTORS INFLUENCING THE GROWING INTEREST IN DATA MINING 10 LIMITATIONS OF DATA MINING 11 HOW DATA MINING WORKS 12 DATA MINING TECHNIQUES 13 ADVANTAGES OF DATA MINING 14 DATA MINING ISSUES 14 CONCLUSION 15 REFERENCES 15 SECTION 1 Introduction We are in the information age and as the demand for information and knowledge increases
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Policies and procedures in response to accidents‚ incidents and emergencies and illness. POLICY – We follow the guidelines in reporting injuries‚ diseases and dangerous occurrences (RIDDOR) for reporting of accidents and incidents Procedures. Accident book: is kept safely and accessibly; Is accessible to staff and volunteers‚ who know how to complete it; and it Is reviewed at least half termly to identify any potential or actual hazards. All accidents recorded are shown to the parent on collection
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