energy innovations and solutions have been hindered by lack of research data on how people use electricity in their homes during the course of the day. But for the past two years‚ one U.S. university has attacked the problem directly. Students and faculty conducting energy and smart grid research at the University of Texas have had access to a treasure trove of knowledge found nowhere else on earth: billions of time-stamped data records from the Pecan Street Research Institute’s original field research
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DATA MINING FOR POTENTIAL CUSTOMERS: East – West Airlines/Telcon Jermaine Paul 12/12/2013 BUSINESS PROBLEM East-West Airlines (EA) is entering into partnership with the cellular service provider‚ Telcon‚ by marketing their service through direct mail. In order to achieve this‚ EA dataset is provided to categorize their customers to identify which ones would be likely to purchase Telcon’s services through direct mail. If the accurate categorization is done the partnership will save
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Benefits of Fleet Management Data Integration NAME DBM 502 University of Phoenix Benefits of Fleet Management Data Integration Abstract Huffman Trucking maintains extensive vehicle fleet maintenance logs‚ with data on vehicles‚ parts‚ tires‚ maintenance‚ warranty‚ costs and dates of service. Management wants to know whether it would be strategically advisable to integrate this information into their current data warehouse and how to leverage it. Investigation shows that there could be significant
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Data warehousing and current trends Submitted to: Mr. S. Ramanathan TABLE OF CONTENTS 1. Executive Summary 2. Data warehousing basics‚ difference from database and its business implication 3. Data mining‚ businesses using it and how 4. ETL technology‚ businesses using it and how 5. Tools used 6. Data mart and difference in business implication 7. References EXECUTIVE SUMMARY This study takes an insight into the usage of data warehousing and data mining
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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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* Stands for "Database Management System." In short‚ a DBMS is a database program. Technically speaking‚ it is a software system that uses a standard method of cataloging‚ retrieving‚ and running queries on data. The DBMS manages incoming data‚ organizes it‚ and provides ways for the data to be modified or extracted by users or other programs. Some DBMS examples include MySQL‚ PostgreSQL‚ Microsoft Access‚ SQL Server‚ FileMaker‚ Oracle‚ RDBMS‚ dBASE‚ Clipper‚ and FoxPro. Since there are
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manage large volumes of business data. The use of database systems in supporting applications that employ query based report generation continues to be the main traditional use of this technology. However‚ the size and volume of data being managed raises new and interesting issues. Can we utilize methods wherein the data can 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
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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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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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