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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structured data‚ accept queries from users‚ and respond to those queries. A typical DBMS has the following features (Stair and Reynolds‚ 2004): Provides a way to structure data as records‚ tables‚ or objects Accepts data input from operators and stores that data for later retrieval Provides query languages for searching‚ sorting‚ reporting‚ and other "decision support" activities that help users correlate and make sense of collected data Provides multi-user access to data‚ along with
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supply 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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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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file processing system are: * Both systems contain a collection of data and a set of programs which access that data. A DBMS coordinates both the physical and the logical access to the data‚ whereas a file-processing system coordinates only the physical access. * A DBMS reduces the amount of data duplication by ensuring that a physical piece of data is available to all programs authorized to have access to it‚ whereas data written by one program in a file-processing system may not be readable
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Chapter: Chapter01: Organizational Performance: IT Support and Applications Multiple Choice 1. To survive and succeed in the New Economy‚ Orbis Inc.’s supply chain model was transformed from a: a) hub-like supply chain to a linear supply chain. b) linear supply chain to a hub-like supply chain. c) multiple layer supply chain to a single layer supply chain. d) single layer supply chain to a multiple layer supply chain. e) spoke like Ans: b Section Ref 1-1 Difficulty: Moderate
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are companies unsure/skeptical on how to proceed with "Big Data"? Answer: Although organizations are increasingly becoming aware of the power that “Big Data” has or can bring‚ they are still unsure how to use it in their situation. They feel their organization is not ready. One of more of the three scenarios is possible. Companies may have a lot of data but they fail to read or decipher it correctly. Perhaps these companies invested in data warehousing and other such programs mindlessly without verying
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Steps in the data preparation process. Editing involves reviewing questionnaires to increase accuracy and precision. It consists of screening questionnaires to identify illegible‚ incomplete‚ inconsistent‚ or ambiguous responses. Responses may be illegible if they have been poorly recorded‚ such as answers to unstructured or open-ended questions. Likewise‚ questionnaires may be incomplete to varying degrees. A few or many questions may be unanswered. At this stage‚ the researcher makes a preliminary
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Data Collection Introduction Review of Literature The first peer-reviewed article was showing how in the 1950s‚ SUV’s (sport utility vehicle) sales increased tremendously with baby boomers. People were in need of larger vehicles to accommodate their entire family. This was not just for domestic vehicles this also included foreign vehicle. With so many people interested in purchasing the SUV’s‚ this led to other car companies designing more comfortable‚ larger vehicles. Another peer-reviewed
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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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