fluxicon Process Mining Tutorial Copyright © 2013 Fluxicon fluxicon Goals of this tutorial • Understand phases of process mining analysis • Be able to get started and play around with your own data fluxicon Outline 1. Example Scenario 2. Roadmap 3. Hands-on Session 4. Take-away Points fluxicon Example Scenario Purchasing process ERP Requester Requester Manager Purchasing Agent Supplier Financial Manager fluxicon Problems 1. Inefficient
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MSU-Iligan Institute of Technology College of Business Administration and Accountancy School of Graduate Studies MASTER IN BUSINESS MANAGEMENT PROGRAM Iligan City REAL WORLD CASE 1: Toyota Europe‚ Campbell Soup Company‚ Sony Pictures‚ and W.W. Grainger. Making the Case for Enterprise Architects Toyota Europe‚ Campbell Soup Company‚ Sony Pictures‚ and W.W. Grainger. Making the Case for Enterprise Architects Submitted to: Professor Adrian Galido‚ PhD Submitted by: Sandee Angeli
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Student’s Name: Nevine El Toukhi Class : 45C Case 01 : Predicting Performance Alix’s Problem Alix Maher is the new admissions director at a small‚ highly selective New England College. She has a bachelor’s degree in education and a recent Master’s Degree in educational administration. But she has no prior experience in college admissions. In spite of Alix’s predecessor had given Scholastic Aptitude Test (SAT)‚ scores (40 %)‚ weights to student selection criteria; Alix has serious reservations
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Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. So‚ data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation of technology developed
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Data Mining On Medical Domain Smita Malik‚ Karishma Naik‚ Archa Ghodge‚ Shivani Gaunker Shree Rayeshwar Institute of Engineering & Information Technology Shiroda‚ Goa‚ India. Smilemalik777@gmail.com; naikkarishma39@gmail.com; archaghodge@gmail.com; shivanigaunker@gmail.com Abstract-The successful application of data mining in highly visible fields like retail‚ marketing & e-business have led to the popularity of its use in knowledge discovery in databases (KDD) in other industries
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Data Mining Assignment 4 Shauna N. Hines Dr. Progress Mtshali Info Syst Decision-Making December 7‚ 2012 Benefits of Data Mining Data mining is defined as “a process that uses statistical‚ mathematical‚ artificial intelligence‚ and machine-learning techniques to extract and identify useful information and subsequent knowledge from large databases‚ including data warehouses” (Turban & Volonino‚ 2011). The information identified using data mining includes patterns indicating trends‚ correlations
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CS 450 Data Mining‚ Fall 2014 Take-Home Test N#1 Date: September 22nd‚ 2014 Final deadline for submission September 29th‚ 2014 Weighting: 5% Total number of points: 100 Instructions: 1. Attempt all questions. 2. This is an individual test. No collaboration is permitted for assessment items. All submitted materials must be a result of your own work. Part I Question 1 [20 points] Discuss whether or not each of the following activities is a data mining task. • Dividing
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Enron Case Answer 1. Who were the key stakeholders involved in‚ or affected by‚ the collapse of Enron? How and to what degree were they hurt or helped by the actions of Enron management? Outline: Key stakeholders involved or affected by the collapse of Enron How were the key stakeholders hurt or helped by the actions of Enron management The degree of Enron management actions’ hurt or helps to the key stakeholders The key stakeholders involved or affected by the collapse of Enron were thousands
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necessity for a businesses trying to maximize its profits. A new‚ and important‚ tool in gaining this knowledge is Data Mining. Data Mining is a set of automated procedures used to find previously unknown patterns and relationships in data. These patterns and relationships‚ once extracted‚ can be used to make valid predictions about the behavior of the customer. Data Mining is generally used for four main tasks: (1) to improve the process of making new customers and retaining customers; (2) to
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In the case study‚ Sergeant Williams did not make a sound decision because he knew that officer Tibet engaged in extra-marital affairs since his colleagues often referred to him as a Lady’s Man. However‚ Officer Tibet was the best field officer and that the attractive Officer Robert had a lot of common sense and a "no-nonsense" demeanor to flirtatious male officers. Therefore‚ the sergeant assumed she was not likely to give in to any inappropriate approaches that Officer Tibet would make towards
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