the stock prices by using trends‚ patterns‚ moving averages observed from historical data. However‚ there have been a certain number of people criticizing the use of past data. Among these people‚ a French mathematician‚ Louis Bachelier raised a theory called Efficient Market Hypothesis more than a century ago. The theory states that stock prices follow a random walk‚ which discouraged the study of historical data. This is very controversial and has led to an ever lasting dispute about the reliability
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chain management are major challenges because many foods have relatively short shelf life than other products. This article give me an example of how Coca Cola Japan Group‚ which is using advanced data warehousing techniques provided by Teradata ‚ a hardware and software vendor specializing in data warehousing and analytic applications to improve the vending business. The article has three parts: The first part introduced Coca Cola Japan Group’s vending market faces new and increasing competition
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DATA MINING REPORT A Comparison of K-means and DBSCAN Algorithm Data Mining with Iris Data Set Using K-Means Cluster method within Weak Data Mining Toolkit. Team Task ......................................................................................................................................... 3 1.0 Introduction ................................................................................................................................. 3 2.0 Related Works ................
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contains only three base cells: (1) (a1‚ b2‚ c3‚ d4; ...‚ d9‚ d10)‚ (2) (a1‚ c2‚ b3‚ d4‚ ...‚ d9‚ d10)‚ and (3) (b1‚ c2‚ b3‚ d4‚ ...‚ d9‚ d10)‚ where a_i != b_i‚ b_i != c_i‚ etc. The measure of the cube is count. 1‚ How many nonempty cuboids will a full data cube contain? Answer: 210 = 1024 2‚ How many nonempty aggregate (i.e.‚ non-base) cells will a full cube contain? Answer: There will be 3 ∗ 210 − 6 ∗ 27 − 3 = 2301 nonempty aggregate cells in the full cube. The number of cells overlapping twice is 27
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Data warehousing logical design Mirjana Mazuran mazuran@elet.polimi.it December 15‚ 2009 1/18 Outline Data Warehouse logical design ROLAP model star schema snowflake schema Exercise 1: wine company Exercise 2: real estate agency 2/18 Introduction Logical design Starting from the conceptual design it is necessary to determin the logical schema of data We use ROLAP (Relational On-Line Analytical Processing) model to represent multidimensional data ROLAP uses the relational
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Company Information Applebee’s: Applebee’s International‚ Inc.‚ is an American company which develops‚ franchises‚ and operates the Applebee’s Neighborhood Grill and Bar restaurant chain. As of September 2011‚ there were 2‚010 restaurants operating system-wide in the United States‚ one U.S. territory and 14 other countries. The company is headquartered in Kansas City‚ Missouri after moving from Lenexa‚ Kansas in September 2011. The Applebee’s concept focuses on casual dining‚ with mainstream American
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com/Articles.nsf/aid/BLACP01 11 Steps to Successful Data Warehousing Mining your corporate data for valuable customer information can improve your business performance. But it’s not as simple as it sounds. By Phillip Blackwood There are 4 reader comments on this topic. Add yours! More and more companies are using data warehousing as a strategy tool to help them win new customers‚ develop new products‚ and lower costs. Searching through mountains of data generated by corporate transaction systems can
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to create and operate data warehouses such as those described in the case? Do you see any disadvantages? Is there any reason that all companies shouldn’t use data warehousing technology? Information is the most important tool when making business decisions. As O’Brien and Marakas stated‚ “Today’s business enterprises cannot survive or succeed without quality data about their internal operations and external environment.” Companies that have large amounts of available data can use the information
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with Data Mining Abstract Banking and finance institutions are growing very fast in this globalization era. Mergers‚ acquisitions‚ globalization have made these institutions bigger. No doubt‚ the data also grow real huge and more varied. Big data storage such as data warehouse and data marts are provided to give a solution on big data storage. On the other sides‚ those data are needed to be analyzed. Business intelligence finally comes in as a solution in analyzing those huge data. Business
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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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