...2013 Submitted To: Prof. Raleigh 06/07/2013 Text Mining Submitted By: Roshan Bhattachan What challenges does the increase in unstructured data present for businesses? Text mining is the discovery of pattern and relationships from large set of unstructured data-the kind of data we generate in emails, phone conversation, blog posting, online customer surveys, and tweets (Laudon & Laudon, 2012). These unstructured data contains lots of useful information, and businesses can use this information to make a better decision making. The challenges for today businesses are how they can make best use of this unstructured information. It’s not a piece of cake to get information out easily because there are millions of information over the internet, and the success of businesses lies in how effectively and efficiently they can process and analyze this information , and use it to make better decision making. It’s a complex and rigorous tasks, and needs people time and money to take out best of information from this unstructured data. How does text-mining improve decision making? Text mining tools are now available to help businesses analyze unstructured data. These tools are able to extract key elements from large unstructured data sets, discover patterns and relationship, and summarize the information. For example: JetBlue in 2007 experienced a number of customer discontent which resulted in large number flight cancelation. It received around 15000 emails per day, and...
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...Data Mining Data mining began with the advent of databases. Databases are warehouses full of computer data. Computer scientists began to realize that this data contains patterns and relationship to other sets of data. As computer technology emerged, data was extracted into useful information. Often, hidden relationships began to appear. Once this data became known and useful, industries grew around data mining. Data mining is a million dollar business aimed at improving marketing, research, criminal apprehension, fraud detection and other applications. History of Data Mining Computers began to be more widely used in the 1960’s. Computers were used to collect and store data. The data was stored on tapes and disks. The companies and organizations began to wonder about the data that was stored. They wanted to know about past sales, past performances and other pertinent information that was stored on these tapes and disks. The next step was to find an accurate way to retrieve the needed information without manually reading all the data. The next step in this quest came in the 1980’s with relational databases and structured queries. Query language could be used to find out more of what was in the data. The companies and organizations could now identify what has happened in the past. They also wanted to know how to apply this knowledge to future predictions based on past performances. In 1989, the first knowledge discovery workshop was held in Detroit (SQL Data Mining, 2012)...
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...An Overview of Data Mining Techniques Page 1 of 48 An Overview of Data Mining Techniques Excerpted from the book Building Data Mining Applications for CRM by Alex Berson, Stephen Smith, and Kurt Thearling Introduction This overview provides a description of some of the most common data mining algorithms in use today. We have broken the discussion into two sections, each with a specific theme: Classical Techniques: Statistics, Neighborhoods and Clustering Next Generation Techniques: Trees, Networks and Rules Each section will describe a number of data mining algorithms at a high level, focusing on the "big picture" so that the reader will be able to understand how each algorithm fits into the landscape of data mining techniques. Overall, six broad classes of data mining algorithms are covered. Although there are a number of other algorithms and many variations of the techniques described, one of the algorithms from this group of six is almost always used in real world deployments of data mining systems. I. Classical Techniques: Statistics, Neighborhoods and Clustering 1.1. The Classics These two sections have been broken up based on when the data mining technique was developed and when it became technically mature enough to be used for business, especially for aiding in the optimization of customer relationship management systems. Thus this section contains descriptions of techniques that have classically been used for decades the next section represents techniques...
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...DATA MINING Generally, data mining is the process of analyzing data from different perspectives and summarizing it into useful information. Data mining software is one of a number of tools for analyzing data. It allows users to analyze data from many different dimensions or angels, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding patterns among dozens of fields in large databases that are similar to one another. Data is any facts, numbers, or text that can be processed by a computer so in general it makes it easier for a company or business to see what the majority of customers want at a time. It’s almost like a survey that we don’t realize we are taking. I think it really can benefit consumers because we can walk into a place of business and see what we want on the shelves because it is in demand. Even better, the things we don’t want to purchase are not there because there is no demand for it. It gives us the choice to be heard and have a say in making decisions on things that impact us most. Information can be converted into knowledge about historical patterns and future trends. For example, summary information on retail supermarket sales can be analyzed in light of promotional efforts to provide knowledge of consumer buying behavior. Thus, a manufacturer or retailer could determine which items are most susceptible to promotional efforts. I don’t think data...
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...a renowned management guru. In this new era, data collection is not as hard as earlier day. Data can be collected easily by various ways, such as, censor, bar code scanner, web browser, online survey, and many more. Business entity sitting on large amount of data wondering,...
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...INTRODUCTION TO BUSINESS ANALYTICS Sumeet Gupta Associate Professor Indian Institute of Management Raipur Outline • Business Analytics and its Applications • Analytics using Data Mining Techniques • Working with R BUSINESS ANALYTICS AND ITS APPLICATIONS What is Business Analytics? Analytics is the use of: data, information technology, statistical analysis, quantitative methods, and mathematical or computer-based models to help managers gain improved insight about their business operations and make better, fact-based decisions. Evolution of Business Analytics? • Operations research • Management science • Business intelligence • Decision support systems • Personal computer software Application Areas of Business Analytics • Management of customer relationships • Financial and marketing activities • Supply chain management • Human resource planning • Pricing decisions • Sport team game strategies Why Business Analytics? • There is a strong relationship of BA with: • profitability of businesses • revenue of businesses • shareholder return • BA enhances understanding of data • BA is vital for businesses to remain competitive • BA enables creation of informative reports Global Warming Poll Winner Sales Revenue Predicting Customer Churn Credit Card Fraud Loan Default Prediction Managing Employee Retention Market Segmentation Medical Imaging Analyzing Tweets stylus ...
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...Coping with Continuous Change in the Business Environment CHANDOS KNOWLEDGE MANAGEMENT SERIES Series Editor: Melinda Taylor (email: melindataylor@chandospublishing.com) Chandos’ new series of books are aimed at all those individuals interested in knowledge management. They have been specially commissioned to provide the reader with an authoritative view of current thinking. If you would like a full listing of current and forthcoming titles, please visit our web site www.chandospublishing.com or contact Hannah Grace-Williams on email info@chandospublishing.com or telephone number +44 (0) 1993 848726. New authors: we are always pleased to receive ideas for new titles; if you would like to write a book for Chandos, please contact Dr Glyn Jones on email gjones@chandospublishing.com or telephone number +44 (0) 1993 848726. Bulk orders: some organisations buy a number of copies of our books. If you are interested in doing this, we would be pleased to discuss a discount. Please contact Hannah Grace-Williams on email info@chandospublishing.com or telephone number +44 (0) 1993 848726. Coping with Continuous Change in the Business Environment Knowledge management and knowledge management technology ANTONIE BOTHA DERRICK KOURIE AND RETHA SNYMAN Chandos Publishing Oxford · England Chandos Publishing (Oxford) Limited TBAC Business Centre Avenue 4 Station Lane Witney Oxford OX28 4BN UK Tel: +44 (0) 1993 848726 Fax: +44 (0) 1865 884448 Email:...
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...operations” (FLA Grading Rubric, n.d., p. 2) These areas should help catapult your company to the status of a fortune 500 company. We would be known worldwide as one of the companies in America that has what it takes to not only compete in a global market, but be sustainable in a global market. “Fortune magazine takes into account the businesses' growth, as measured by stock earnings and investment returns, assets, revenue and profit when compiling the list.” (Tran, n.d., para. 3) Strategic Outsourcing If order to businesses to remain competitive, they must walk a fine line between costs and quality. Outsourcing plays an intricate part in this process. First off what is outsourcing? “Outsourcing has evolved beyond being viewed as a purely tactical exercise to reduce costs and increase operational efficiencies.” (Singhal, n.d., para. 1) SCF plans on utilizing strategic outsourcing to “adapt flexibly to business change, improve quality and productivity, respond quickly to competition, and penetrate new markets”. (Singhal, n.d., p. 1) This service can encompass anything from “Application Development and Maintenance (ADM) to business process outsourcing to setting up turnkey IT centers on a BOT model (Build-Operate-Transfer), to business re-engineering”. (Singhal, n.d., p. 1) Outsourcing can take...
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...FILE ORGANIZATION TERMS AND CONCEPTS THE DATA HIERARCHY A computer system organizes data in a hierarchy that starts with bits and bytes and progresses to fields, records, files, and databases * A bit represents the smallest unit of data a computer can handle * A group of bits, called a byte, represents a single character, which can be a letter, a number, or another symbol (A,2?,S) * A grouping of characters into a word, a group of words, or a complete number (such as a person’s name or age) is called a field Ex: employee Last name, Customer Account number * A group of related fields, such as the student’s name, the course taken, the date, and the grade, comprises a record; Ex: There will be one record for every one * A group of records of the same type is called a file. Ex: Employee Benefits file, Employee payroll file * Database: A group of related files about a specific entity Ex: HR database PROBLEMS WITH THE TRADITIONAL FILE ENVIRONMENT In most organizations, systems tended to grow independently without a company-wide plan. Accounting, finance, manufacturing, human resources, and sales and marketing all developed their own systems and data files. Figure 6-2 illustrates the traditional approach to information processing * In the company as a whole, this process led to multiple master files created, maintained, and operated by separate divisions or departments. As this process goes on for 5 or 10 years, the organization is saddled...
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...SPECIAL ISSUE: BUSINESS INTELLIGENCE RESEARCH BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT Hsinchun Chen Eller College of Management, University of Arizona, Tucson, AZ 85721 U.S.A. {hchen@eller.arizona.edu} Roger H. L. Chiang Carl H. Lindner College of Business, University of Cincinnati, Cincinnati, OH 45221-0211 U.S.A. {chianghl@ucmail.uc.edu} Veda C. Storey J. Mack Robinson College of Business, Georgia State University, Atlanta, GA 30302-4015 U.S.A. {vstorey@gsu.edu} Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research framework. Keywords:...
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...SPECIAL ISSUE: BUSINESS INTELLIGENCE RESEARCH BUSINESS INTELLIGENCE AND ANALYTICS: FROM BIG DATA TO BIG IMPACT Hsinchun Chen Eller College of Management, University of Arizona, Tucson, AZ 85721 U.S.A. {hchen@eller.arizona.edu} Roger H. L. Chiang Carl H. Lindner College of Business, University of Cincinnati, Cincinnati, OH 45221-0211 U.S.A. {chianghl@ucmail.uc.edu} Veda C. Storey J. Mack Robinson College of Business, Georgia State University, Atlanta, GA 30302-4015 U.S.A. {vstorey@gsu.edu} Business intelligence and analytics (BI&A) has emerged as an important area of study for both practitioners and researchers, reflecting the magnitude and impact of data-related problems to be solved in contemporary business organizations. This introduction to the MIS Quarterly Special Issue on Business Intelligence Research first provides a framework that identifies the evolution, applications, and emerging research areas of BI&A. BI&A 1.0, BI&A 2.0, and BI&A 3.0 are defined and described in terms of their key characteristics and capabilities. Current research in BI&A is analyzed and challenges and opportunities associated with BI&A research and education are identified. We also report a bibliometric study of critical BI&A publications, researchers, and research topics based on more than a decade of related academic and industry publications. Finally, the six articles that comprise this special issue are introduced and characterized in terms of the proposed BI&A research...
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...IEEE International Conference on Data Engineering Business Intelligence from Voice of Customer L. Venkata Subramaniam, Tanveer A. Faruquie, Shajith Ikbal, Shantanu Godbole, Mukesh K. Mohania IBM India Research Lab, India {lvsubram,ftanveer,shajmoha,shantanugodbole,mkmukesh}@in.ibm.com Abstract— In this paper, we present a first of a kind system, called Business Intelligence from Voice of Customer (BIVoC), that can: 1) combine unstructured information and structured information in an information intensive enterprise and 2) derive richer business insights from the combined data. Unstructured information, in this paper, refers to Voice of Customer (VoC) obtained from interaction of customer with enterprise namely, conversation with call-center agents, email, and sms. Structured database reflect only those business variables that are static over (a longer window of) time such as, educational qualification, age group, and employment details. In contrast, a combination of unstructured and structured data provide access to business variables that reflect upto date dynamic requirements of the customers and more importantly indicate trends that are difficult to derive from a larger population of customers through any other means. For example, some of the variables reflected in unstructured data are problem/interest in a certain product, expression of dissatisfaction with the business provided, and some unexplored category of people showing certain interest/problem...
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...Math * Analytical * Emotional * Bodily * Cultural Theory of Multiple Intelligence: * Verbal * Math * Analytical * Emotional * Bodily * Cultural Interaction? * Does it act like a human? Areas of AI: * Natural Language Processing- Build language systems of Interaction for business * Ex. Google Translate * Text Mining * Voice generation and recognition (SIRI) * Analyzes input and builds a response * Must think about: * Speech-phonology * How words are formed-morphology * How sentences are formed-Grammar syntax * What do words and sentences mean- Semantics * How does context affect language?- Pragmatics * Speech Recognition * Robotics and Sensory Systems * Visual Recognition * Ie. Baxter folding shirt * Used by customs * Intelligent Computer Aided Instruction * Neural Computing * Build software and hardware systems that simulate the working of the brain through neurons. * Mimics brain connections * Neural connections are like a network INSERT NOTES FROM NOTEBOOK DSS: Bounded Reality- related to satisficing. Humans have a limited capacity for thinking- but rationality might...
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... Praise “A must-read resource for anyone who is serious about embracing the opportunity of big data.” — Craig Vaughan Global Vice President at SAP “This timely book says out loud what has finally become apparent: in the modern world, Data is Business, and you can no longer think business without thinking data. Read this book and you will understand the Science behind thinking data.” — Ron Bekkerman Chief Data Officer at Carmel Ventures “A great book for business managers who lead or interact with data scientists, who wish to better understand the principals and algorithms available without the technical details of single-disciplinary books.” — Ronny Kohavi Partner Architect at Microsoft Online Services Division “Provost and Fawcett have distilled their mastery of both the art and science of real-world data analysis into an unrivalled introduction to the field.” —Geoff Webb Editor-in-Chief of Data Mining and Knowledge Discovery Journal “I would love it if everyone I had to work with had read this book.” — Claudia Perlich Chief Scientist of M6D (Media6Degrees) and Advertising Research Foundation Innovation Award Grand Winner (2013) www.it-ebooks.info “A foundational piece in the fast developing world of Data Science. A must read for anyone interested in the Big Data revolution." —Justin Gapper Business Unit Analytics Manager at Teledyne Scientific and Imaging “The authors, both renowned experts in data science before it had a name, have taken a complex topic and made it accessible...
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...Mining Industry Case Analysis | Business Ethics in a Global Context | Presented To: Dr. Jang Singh | | | | Executive Summary This report will examine the Mining Industry via ethical perspectives. This report includes a brief overview of the industry followed by an evaluation of the Mining industry’s value chain; including an environmental analysis of a mining company, as well as an evaluation of the industry’s corporate social responsibility, corporate social responsiveness and finally the corporate social performance. The Mining Industry is one of the World’s largest industries. The ‘idea’ of mining dates back to the beginning stage of civilization. Some examples of early mining can be found in Egypt, Europe and the Philippines. As of now, top mining countries are South Africa, Russia, Australia, Ukraine and Guinea. This industry faces constant technology advancement, consequently it is an expensive investment, with large profit. The Mining Industry can be controversial when looked through an ethical lens. This Industry is analysed through four perspectives. * The utilitarianism perspective, an act is morally right if the outcome benefits the greatest amount of people; * The rights perspective, basically, important entitlements that should be respected and protected in every action; * The justice perspective, fair treatment of individuals in a situation where everyone is involved and gets what they deserve to; * The virtue perspective, morally...
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