{"product_id":"heuristics-in-analytics-isbn-9781118347607","title":"Heuristics in Analytics","description":"\u003cb\u003eEmploy heuristic adjustments for truly accurate analysis\u003c\/b\u003e  \u003cp\u003e\u003ci\u003eHeuristics in Analytics\u003c\/i\u003e presents an approach to analysis that accounts for the randomness of business and the competitive marketplace, creating a model that more accurately reflects the scenario at hand. With an emphasis on the importance of proper analytical tools, the book describes the analytical process from exploratory analysis through model developments, to deployments and possible outcomes. Beginning with an introduction to heuristic concepts, readers will find heuristics applied to statistics and probability, mathematics, stochastic, and artificial intelligence models, ending with the knowledge applications that solve business problems. Case studies illustrate the everyday application and implication of the techniques presented, while the heuristic approach is integrated into analytical modeling, graph analysis, text analytics, and more.\u003c\/p\u003e \u003cp\u003eRobust analytics has become crucial in the corporate environment, and randomness plays an enormous role in business and the competitive marketplace. Failing to account for randomness can steer a model in an entirely wrong direction, negatively affecting the final outcome and potentially devastating the bottom line. \u003ci\u003eHeuristics in Analytics\u003c\/i\u003e describes how the heuristic characteristics of analysis can be overcome with problem design, math and statistics, helping readers to:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eRealize just how random the world is, and how unplanned events can affect analysis\u003c\/li\u003e \u003cli\u003eIntegrate heuristic and analytical approaches to modeling and problem solving\u003c\/li\u003e \u003cli\u003eDiscover how graph analysis is applied in real-world scenarios around the globe\u003c\/li\u003e \u003cli\u003eApply analytical knowledge to customer behavior, insolvency prevention, fraud detection, and more\u003c\/li\u003e \u003cli\u003eUnderstand how text analytics can be applied to increase the business knowledge\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eEvery single factor, no matter how large or how small, must be taken into account when modeling a scenario or event—even the unknowns. The presence or absence of even a single detail can dramatically alter eventual outcomes. From raw data to final report, \u003ci\u003eHeuristics in Analytics\u003c\/i\u003e contains the information analysts need to improve accuracy, and ultimately, predictive, and descriptive power.\u003c\/p\u003e \u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003eAcknowledgments xix\u003c\/p\u003e \u003cp\u003eAbout the Authors xxiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1: Introduction 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eThe Monty Hall Problem 5\u003c\/p\u003e \u003cp\u003eEvolving Analytics 8\u003c\/p\u003e \u003cp\u003eSummary 18\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2: Unplanned Events, Heuristics, and the Randomness in Our World 23\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eHeuristics Concepts 26\u003c\/p\u003e \u003cp\u003eThe Butterfly Effect 30\u003c\/p\u003e \u003cp\u003eRandom Walks 37\u003c\/p\u003e \u003cp\u003eSummary 44\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3: The Heuristic Approach and Why We Use It 45\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eHeuristics in Computing 47\u003c\/p\u003e \u003cp\u003eHeuristic Problem-Solving Methods 51\u003c\/p\u003e \u003cp\u003eGenetic Algorithms: A Formal Heuristic Approach 54\u003c\/p\u003e \u003cp\u003eSummary 67\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4: The Analytical Approach 69\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction to Analytical Modeling 71\u003c\/p\u003e \u003cp\u003eThe Competitive-Intelligence Cycle 74\u003c\/p\u003e \u003cp\u003eSummary 97\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5: Knowledge Applications That Solve Business Problems 101\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCustomer Behavior Segmentation 102\u003c\/p\u003e \u003cp\u003eCollection Models 106\u003c\/p\u003e \u003cp\u003eInsolvency Prevention 113\u003c\/p\u003e \u003cp\u003eFraud-Propensity Models 120\u003c\/p\u003e \u003cp\u003eSummary 127\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6: The Graph Analysis Approach 129\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eIntroduction to Graph Analysis 130\u003c\/p\u003e \u003cp\u003eSummary 143\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7: Graph Analysis Case Studies 147\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eCase Study: Identifying Influencers in Telecommunications 149\u003c\/p\u003e \u003cp\u003eCase Study: Claim Validity Detection in Motor Insurance 162\u003c\/p\u003e \u003cp\u003eCase Study: Fraud Identification in Mobile Operations 178\u003c\/p\u003e \u003cp\u003eSummary 188\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8: Text Analytics 191\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eText Analytics in the Competitive-Intelligence Cycle 193\u003c\/p\u003e \u003cp\u003eLinguistic Models 198\u003c\/p\u003e \u003cp\u003eText-Mining Models 200\u003c\/p\u003e \u003cp\u003eSummary 207\u003c\/p\u003e \u003cp\u003eBibliography 209\u003c\/p\u003e \u003cp\u003eIndex 217\u003c\/p\u003e  \u003cp\u003e\u003cb\u003eCARLOS ANDRE REIS PINHEIRO\u003c\/b\u003e is Visiting Professor at KU Leuven, Belgium. He headed the Analytical Lab at Oi in Brazil, one of the largest telecommunications companies in Latin America. Pinheiro has conducted Postdoctoral Research at Katholieke Universiteit Leuven, Belgium, Université de Savoie, France and Dublin City University, Ireland. He holds a PhD in Engineering from Federal University of Rio de Janeiro, Brazil. He worked at Brazil Telecom for almost ten years and also accomplished postdoctoral research at IMPA, Brazil, one of the most prestigious mathematical institutions in the world. He has published several papers in international journals and conferences and has four books (all in Portuguese) that focus on the internet, database, web warehousing, and analytical intelligence. He is the author of \u003ci\u003eSocial Network Analysis in Telecommunications\u003c\/i\u003e,\u003ci\u003e\u003c\/i\u003e published by Wiley\u003ci\u003e.\u003c\/i\u003e \u003c\/p\u003e\u003cp\u003e\u003cb\u003eFIONA McNEILL\u003c\/b\u003e has applied analytics to business problems since she began her career in 1992 and has consistently helped companies benefit from strategic use of data and analytics. Throughout her career, she has been affiliated with data and technology companies, from information and survey providers, IBM Global Services and for over fifteen years, at SAS. McNeill has published in academic journals, conducted education seminars and presented at both academic and industry conferences over the course of her career. She holds an M.A. in Quantitative Behavioral Geography from McMaster University, and graduated cum laude with a B.Sc. in Bio-Physical Systems, University of Toronto.    \u003c\/p\u003e\u003cp\u003eIn \u003ci\u003eHeuristics in Analytics,\u003c\/i\u003e renowned telecommunications experts Carlos Andre Reis Pinheiro and Fiona McNeill describe analytic processes and how they fit into the heuristic world around us. In spite of the strong heuristic characteristics of the analytical processes, \u003ci\u003eHeuristics in Analytics\u003c\/i\u003e emphasizes the need to have the proper tools to engage analytics and shows how to overcome heuristic characteristics through the use of mathematics and statistics. \u003c\/p\u003e\u003cp\u003eThis straightforward book explores how important it is to properly consider the randomness and the heuristic characteristics in analytics and how crucial analytics are for companies and corporate environments. Drawing from the authors' years of experience, \u003ci\u003eHeuristics in Analytics\u003c\/i\u003e looks at: \u003c\/p\u003e\u003cul\u003e \u003cli\u003eUnplanned events, heuristics, and the randomness in our world\u003c\/li\u003e \u003cli\u003eThe analytical approach\u003c\/li\u003e \u003cli\u003eThe competitive intelligence cycle\u003c\/li\u003e \u003cli\u003eKnowledge applications that solve business problems\u003c\/li\u003e \u003cli\u003eCustomer behavioral segmentation\u003c\/li\u003e \u003cli\u003eThe graph analysis approach\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003ePacked with case studies on the entire analytical process using telecom and insurance companies based in Brazil and Ireland, \u003ci\u003eHeuristics in Analytics\u003c\/i\u003e provides CFOs, chief marketing officers, directors of marketing, and business managers with an insider guide to deploying mathematical and statistical models when performing analytics.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989359968485,"sku":"NP9781118347607","price":49.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118347607.jpg?v=1761783809","url":"https:\/\/k12savings.com\/es\/products\/heuristics-in-analytics-isbn-9781118347607","provider":"K12savings","version":"1.0","type":"link"}