MARC Record from marc_columbia

LEADER: 08661cam a2200721Mi 4500
001 14751610
005 20210607151153.0
006 m o d
007 cr cnu---unuuu
008 190223s2019 xx o 000 0 eng d
035 $a(OCoLC)on1088331946
035 $a(NNC)14751610
040 $aEBLCP$beng$epn$cEBLCP$dTYFRS$dUKAHL$dOCLCF$dYDX$dOCLCQ
019 $a1086484681
020 $a9781351973410
020 $a135197341X
020 $a9781315267555$q(electronic bk.)
020 $a1315267551$q(electronic bk.)
020 $a9781351973403$q(electronic bk. ;$qEPUB)
020 $a1351973401$q(electronic bk. ;$qEPUB)
020 $a9781351973397$q(electronic bk. ;$qMobipocket)
020 $a1351973398$q(electronic bk. ;$qMobipocket)
020 $z9781138035485
020 $z1138035483
035 $a(OCoLC)1088331946$z(OCoLC)1086484681
050 4 $aHD30.2
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072 7 $aMAT$x029000$2bisacsh
072 7 $aUB$2bicssc
082 04 $a658.4/52$223
049 $aZCUA
100 1 $aSamaddar, Subhashish.
245 10 $aData Analytics :$bEffective Methods for Presenting Results.
260 $aMilton :$bAuerbach Publications,$c2019.
300 $a1 online resource (175 pages)
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
490 1 $aData Analytics Applications Ser.
588 0 $aPrint version record.
505 0 $aCover; Half Title; Series Page; Title Page; Copyright Page; CONTENTS; PREFACE; EXECUTIVE SUMMARY; EDITORS; CONTRIBUTORS; CHAPTER 1 KNOW YOUR AUDIENCE; Preparing for Your Presentation; Organizing the Presentation; Audience Interaction; CHAPTER 2 PRESENTING RESULTS FROM COMMONLY USED MODELING TECHNIQUES; Regression Analysis; Cluster Analysis; Summary; CHAPTER 3 VISUALIZATION TO IMPROVE ANALYTICS; The Paradox of Visualization; Things Are Not Always as They Seem; The Role of Domain Knowledge; Moving through Complexity; Simplicity Is Hard; Conclusion
505 8 $aCHAPTER 4 MARKETING MODELS-DEMONSTRATING EFFECTIVENESS TO CLIENTSCustom versus Generic Data Fields; Generic Model Visualization; GamerIQ-A Generic Model; Selling the Model; Custom Marketing Models; Do's and Don'ts in Client Meetings; Conclusion; Appendix A: Game Over-AnalyticsIQ Is Proud To Release GamerIQ; Let's Play; GamerIQ; Level Up; How AIQ Data Compares to Other Providers; CHAPTER 5 RESTAURANT MANAGEMENT: CONVINCING MANAGEMENT TO CHANGE; Introduction; Strategy and Operations; Finding and Assessing Performance Improvement Projects; Communicating Results
505 8 $aFrom Marketing Research to Operations ResearchConclusions; CHAPTER 6 PROJECT PRESENTATIONS IN THE ARMED FORCES; Common Types of Analysis in the Armed Forces; Audience, Time, and Complexity Considerations; The Audience; Complexity and Time; Other Examples of Successful Techniques and Slides; Summary; CHAPTER 7 INVENTORY MANAGEMENT-CUSTOMIZING PRESENTATIONS FOR MANAGEMENT LAYERS; Inventory Management at Intel; Review 1: Presenting to My Manager; Review 2: Model Validation; Review 3: Technical Experts; Review 4: Presenting to Senior Management; Summary
505 8 $aCHAPTER 8 EXECUTIVE COMMUNICATION IN PROCESS IMPROVEMENTIntroduction to Lean Six Sigma; Data Availability, Level of Rigor, and Managing Expectations; BBs Are Not Superheroes; GBs Have Day Jobs; Do's and Don'ts of Presenting LSS Work to Leadership; Conclusion; CHAPTER 9 INTERNAL AUDITING-SEEKING ACTION FROM TOP MANAGEMENT TO MITIGATE RISK; Introduction; Use of Analytics in Auditing; Conclusion; CHAPTER 10 CONSUMER LENDING-WINNING PRESENTATIONS TO INVESTORS; The Backdrop; Building the Systems; Audience Drives the Reporting Needs; Analytics, Visualization, and Storytelling
505 8 $aThe Problem with Analysts: Black Swans, ML, and the FutureCHAPTER 11 "AS YOU CAN SEE ... "; Epilogue; INDEX
520 $aIf you are a manager who receives the results of any data analyst's work to help with your decision-making, this book is for you. Anyone playing a role in the field of analytics can benefit from this book as well. In the two decades the editors of this book spent teaching and consulting in the field of analytics, they noticed a critical shortcoming in the communication abilities of many analytics professionals. Specifically, analysts have difficulty in articulating in business terms what their analyses showed and what actionable recommendations were made. When analysts made presentations, they tended to lapse into the technicalities of mathematical procedures, rather than focusing on the strategic and tactical impact and meaning of their work. As analytics has become more mainstream and widespread in organizations, this problem has grown more acute. Data Analytics: Effective Methods for Presenting Results tackles this issue. The editors have used their experience as presenters and audience members who have become lost during presentation. Over the years, they experimented with different ways of presenting analytics work to make a more compelling case to top managers. They have discovered tried and true methods for improving presentations, which they share. The book also presents insights from other analysts and managers who share their own experiences. It is truly a collection of experiences and insight from academics and professionals involved with analytics. The book is not a primer on how to draw the most beautiful charts and graphs or about how to perform any specific kind of analysis. Rather, it shares the experiences of professionals in various industries about how they present their analytics results effectively. They tell their stories on how to win over audiences. The book spans multiple functional areas within a business, and in some cases, it discusses how to adapt presentations to the needs of audiences at different levels of management.
545 0 $aSubhashish Samaddar, PhD, Certified Analytics Professional (CAPª), is a professor of business analytics and operations management in the managerial sciences department of the J. Mack Robinson College of Business at Georgia State University, Atlanta, Georgia, where he was the founding academic director of MS analytics program. He served on the INFORMS' team that created the CAP certification examination administered globally and coedited its first guide book. An internationally reputed and multiple award-winning researcher, teacher, and speaker, he specializes in business analytics, operations and organizational knowledge management, and decision making. A veteran of more than 25 years and a consultant in analytics, he has helped many U.S. organizations-Fortune 100, privately held and governmental agencies-with their analytical needs. He currently teaches business analytics and research methods to undergraduates, MBA and executive master's and doctoral students, and corporate clients. Satish Nargundkar, PhD, is a professor of business analytics in the J. Mack Robinson College of Business at Georgia State University, Atlanta. Over the past three decades, he has helped large and small companies improve their decision-making through analytics. A recipient of multiple awards for teaching and research, he has over 25 years of experience in the areas of analytics, process improvement, and decision support. His research interests are multidisciplinary and include supply chain management, quantitative methods, and the improvement of teaching methods. He is passion ate about excellence in teaching and is sought after as an instructor in executive programs. In his spare time, he enjoys reading, traveling, and photography, and is an instructor in martial arts.
650 0 $aBusiness$xData processing.
650 0 $aBusiness requirements analysis.
650 0 $aBusiness analysts.
650 7 $aCOMPUTERS$xComputer Graphics$xGeneral.$2bisacsh
650 7 $aCOMPUTERS$xDatabase Management$xData Mining.$2bisacsh
650 7 $aMATHEMATICS$xProbability & Statistics$xGeneral.$2bisacsh
650 7 $aBusiness analysts.$2fast$0(OCoLC)fst01743911
650 7 $aBusiness$xData processing.$2fast$0(OCoLC)fst00842293
650 7 $aBusiness requirements analysis.$2fast$0(OCoLC)fst01743099
655 4 $aElectronic books.
700 1 $aNargundkar, Satish.
776 08 $iPrint version:$aSamaddar, Subhashish.$tData Analytics : Effective Methods for Presenting Results.$dMilton : Auerbach Publications, ©2019$z9781138035485
830 0 $aData analytics applications.
856 40 $uhttp://www.columbia.edu/cgi-bin/cul/resolve?clio14751610$zTaylor & Francis eBooks
852 8 $blweb$hEBOOKS