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001 9781315267555
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007 cr cnu---unuuu
008 190223s2019 xx o 000 0 eng d
040 _aOCoLC-P
_beng
_cOCoLC-P
020 _a9781351973410
020 _a135197341X
020 _a9781315267555
_q(electronic bk.)
020 _a1315267551
_q(electronic bk.)
020 _a9781351973403
_q(electronic bk. : EPUB)
020 _a1351973401
_q(electronic bk. : EPUB)
020 _a9781351973397
_q(electronic bk. : Mobipocket)
020 _a1351973398
_q(electronic bk. : Mobipocket)
035 _a(OCoLC)1088331946
035 _a(OCoLC-P)1088331946
050 4 _aHD30.2
072 7 _aCOM
_x012000
_2bisacsh
072 7 _aCOM
_x021030
_2bisacsh
072 7 _aMAT
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_2bisacsh
072 7 _aUB
_2bicssc
082 0 4 _a658.4/52
_223
100 1 _aSamaddar, Subhashish.
_917694
245 1 0 _aData Analytics
_h[electronic resource] :
_bEffective Methods for Presenting Results.
260 _aMilton :
_bAuerbach Publications,
_c2019.
300 _a1 online resource (175 p.).
490 1 _aData Analytics Applications Ser.
500 _aDescription based upon print version of 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.
588 _aOCLC-licensed vendor bibliographic record.
650 0 _aBusiness
_xData processing.
_99331
650 0 _aBusiness requirements analysis.
_917695
650 0 _aBusiness analysts.
_917696
650 7 _aCOMPUTERS / Computer Graphics / General
_2bisacsh
_912490
650 7 _aCOMPUTERS / Database Management / Data Mining
_2bisacsh
_912290
650 7 _aMATHEMATICS / Probability & Statistics / General
_2bisacsh
_96860
700 1 _aNargundkar, Satish.
_917697
856 4 0 _3Taylor & Francis
_uhttps://www.taylorfrancis.com/books/9781315267555
856 4 2 _3OCLC metadata license agreement
_uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
942 _cEBK
999 _c71611
_d71611