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E-raamat: Unstructured Data Analytics: How to Improve Customer Acquisition, Customer Retention, and Fraud Detection and Prevention

  • Formaat: EPUB+DRM
  • Ilmumisaeg: 02-Mar-2018
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119325499
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  • Formaat: EPUB+DRM
  • Ilmumisaeg: 02-Mar-2018
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119325499
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Turn unstructured data into valuable business insight

Unstructured Data Analytics provides an accessible, non-technical introduction to the analysis of unstructured data. Written by global experts in the analytics space, this book presents unstructured data analysis (UDA) concepts in a practical way, highlighting the broad scope of applications across industries, companies, and business functions. The discussion covers key aspects of UDA implementation, beginning with an explanation of the data and the information it provides, then moving into a holistic framework for implementation. Case studies show how real-world companies are leveraging UDA in security and customer management, and provide clear examples of both traditional business applications and newer, more innovative practices.

Roughly 80 percent of today's data is unstructured in the form of emails, chats, social media, audio, and video. These data assets contain a wealth of valuable information that can be used to great advantage, but accessing that data in a meaningful way remains a challenge for many companies. This book provides the baseline knowledge and the practical understanding companies need to put this data to work.

Supported by research with several industry leaders and packed with frontline stories from leading organizations such as Google, Amazon, Spotify, LinkedIn, Pfizer Manulife, AXA, Monster Worldwide, Under Armour, the Houston Rockets, DELL, IBM, and SAS Institute, this book provide a framework for building and implementing a successful UDA center of excellence.

You will learn:





How to increase Customer Acquisition and Customer Retention with UDA The Power of UDA for Fraud Detection and Prevention The Power of UDA in Human Capital Management & Human Resource The Power of UDA in Health Care and Medical Research The Power of UDA in National Security The Power of UDA in Legal Services The Power of UDA for product development The Power of UDA in Sports The future of UDA

From small businesses to large multinational organizations, unstructured data provides the opportunity to gain consumer information straight from the source. Data is only as valuable as it is useful, and a robust, effective UDA strategy is the first step toward gaining the full advantage. Unstructured Data Analytics lays this space open for examination, and provides a solid framework for beginning meaningful analysis.
Foreword xiii
Preface xv
Acknowledgments xix
Chapter 1 The Age of Advanced Business Analytics
1(32)
Introduction
1(4)
Why the Analytics Hype Today?
5(10)
A Short History of Data Analytics
15(7)
What Is the Analytics Age?
22(1)
Interview with Wayne Thompson, Chief Data Scientist at SAS Institute
23(5)
Key Takeaways
28(1)
Notes
29(1)
Further Reading
30(3)
Chapter 2 Unstructured Data Analytics: The Next Frontier of Analytics Innovation
33(36)
Introduction
33(2)
What Is UDA?
35(4)
Why UDA Today?
39(9)
The UDA Industry
48(3)
Uses of UDA
51(1)
How UDA Works
52(2)
Why UDA Is the Next Analytical Frontier?
54(4)
Interview with Seth Grimes on Analytics as the Next Business Frontier
58(2)
UDA Success Stories
60(4)
The Golden Age of UDA
64(1)
Key Takeaways
65(1)
Notes
66(1)
Further Reading
67(2)
Chapter 3 The Framework to Put UDA to Work
69(40)
Introduction
69(1)
Why Have a Framework to Analyze Unstructured Data?
70(2)
The IMPACT Cycle Applied to Unstructured Data
72(9)
Text Parsing Example
81(3)
Interview with Cindy Forbes, Chief Analytics Officer and Executive Vice President at Manulife Financial
84(6)
Case Study
90(16)
Key Takeaways
106(1)
Notes
107(1)
Further Reading
108(1)
Chapter 4 How to increase Customer Acquisition and Retention with UDA
109(48)
The Voice of the Customer: A Goldmine for Understanding Customers
109(2)
Why Should You Care about UDA for Customer Acquisition and Retention?
111(6)
Predictive Models and Online Marketing
117(1)
How Does UDA Applied to Customer Acquisition Work?
118(6)
The Power of UDA for E-mail Response and Ad Optimization
124(1)
How to Drive More Conversion and Engagement with UDA Applied to Content
124(1)
How UDA Applied to Customer Retention (Churn) Works
125(4)
What Is UDA Applied to Customer Acquisition?
129(6)
What Is UDA Applied to Customer Retention (Churn)?
135(1)
The Power of UDA Powered by Virtual Agent
136(2)
Benefits of a Virtual Agent or AI Assistant for Customer Experience
138(1)
Benefits and Case Studies
139(12)
Applying UDA to Your Social Media Presence and Native Ads to Increase Acquisitions
151(2)
Key Takeaways
153(1)
Notes
154(3)
Chapter 5 The Power of UDA to Improve Fraud Detection and Prevention
157(34)
Introduction
157(2)
Why Should You Care about UDA for Fraud Detection and Prevention?
159(4)
Benefits of UDA
163(5)
What Is UDA for Fraud?
168(2)
How UDA Works in Fraud Detection and Prevention
170(3)
UDA Framework for Fraud Detection and Prevention: Insurance
173(3)
Major Fraud Detection and Prevention Techniques
176(3)
Best Practices Using UDA for Fraud Detection and Prevention
179(3)
Interview with Vishwa Kolla, Assistant Vice President Advanced Analytics at John Hancock Financial Services
182(2)
Interview with Diane Deperrois, General Manager South-East and Overseas Region, AXA
184(3)
Key Takeaways
187(2)
Notes
189(1)
Further Reading
189(2)
Chapter 6 The Power of UDA in Human Capital Management
191(28)
Why Should You Care about UDA in Human Resources?
191(2)
What Is UDA in HR?
193(2)
What Is UDA in HR Really About?
195(1)
The Power of UDA in Online Recruitment: Supply and Demand Equation
196(1)
The Power of UDA in Talent Sourcing Analytics
197(8)
The Power of UDA in Talent Acquisition Analytics
205(1)
Artificial Intelligence as a Hiring Assistant
206(1)
The Power of UDA in Talent Retention
207(1)
Interview with Arun Chidambaram, Director of Global workforce intelligence, Pfizer
208(2)
Employee Performance Appraisal Data Review Feedback
210(1)
How UDA Works
211(1)
Benefits of UDA in HR
212(1)
Case Studies
213(1)
Interview with Stephani Kingsmill, Executive Vice President and Chief Human Resource Officer, Manulife
213(3)
Key Takeaways
216(1)
Further Reading
217(2)
Chapter 7 The Power of UDA in the Legal industry
219(18)
Why Should You Care about UDA in Legal Services?
219(5)
What Is UDA Applied to Legal Services?
224(1)
How Does It Work?
224(7)
Benefits and Challenges
231(3)
Key Takeaways
234(1)
Notes
235(1)
Further Reading
235(2)
Chapter 8 The Power of UDA in Healthcare and Medical Research
237(30)
Why Should You Care about UDA in Healthcare?
237(8)
What's UDA in Healthcare?
245(5)
How UDA Works
250(5)
Benefits
255(2)
Interview with Mr. Francois Laviolette, Professor of Computer Science/Director of Big Data Research Centre at Laval University (QC) Canada
257(1)
Interview with Paul Zikopolous, Vice President Big Data Cognitive System at IBM
258(4)
Case Study
262(1)
Key Takeaways
263(1)
Notes
264(1)
Further Reading
265(2)
Chapter 9 The Power of UDA in Product and Service Development
267(40)
Why Should You Care about UDA for Product and Service Development?
267(1)
UDA and Big Data Analytics
268(15)
Interview with Fiona McNeill, Global Product Marketing Manager at SAS Institute
283(14)
What Is UDA Applied to Product Development?
297(3)
How Is UDA Applied to Product Development?
300(1)
How UDA Applied to Product Development Works
301(2)
Key Takeaways
303(1)
Notes
304(3)
Chapter 10 The Power of UDA in National Security
307(20)
National Security: Playground for UDA or Civil Liberty Threat?
307(3)
What Is UDA for National Security?
310(1)
Data Sources of the NSA
310(4)
Why UDA for National Security?
314(6)
Case Studies
320(2)
How UDA Works
322(1)
Key Takeaways
323(1)
Notes
324(1)
Further Reading
325(2)
Chapter 11 The Power of UDA in Sports
327(22)
The Short History of Sports Analytics: Moneyball
328(5)
Why Should You Care about UDA in Sports?
333(5)
What Is UDA in Sports?
338(4)
How It Works
342(1)
Interview with Winston Lin, Director of Strategy and Analytics for the Houston Rockets
343(4)
Key Takeaways
347(1)
Notes
347(1)
Further Reading
348(1)
Chapter 12 The Future of Analytics
349(20)
Harnessing These Evolving Technologies Will Generate Benefits
350(3)
Data Becomes Less Valuable and Analytics Becomes Mainstream
353(2)
Predictive Analytics, AI, Machine Learning, and Deep Learning Become the New Standard
355(3)
People Analytics Becomes a Standard Department in Businesses
358(1)
UDA Becomes More Prevalent in Corporations and Businesses
359(1)
Cognitive Analytics Expansion
359(1)
The Internet of Things Evolves to the Analytics of Things
360(1)
MOOCs and Open Source Software and Applications Will Continue to Explode
361(1)
Blockchain and Analytics Will Solve Social Problems
362(2)
Human-Centered Computing Will Be Normalized
364(1)
Data Governance and Data Security Will Remain the Number-One Risk and Threat
365(1)
Key Takeaways
366(1)
Notes
367(1)
Further Reading
367(2)
Appendix A Tech Corner Details
369(32)
Singular Value Decomposition (SVD) Algorithm and Applications
370(12)
Principal Component Analysis (PCA) and Applications
382(10)
PCA Application to Facial Recognition: EigenFaces
392(2)
QR Factorization Algorithm and Applications
394(5)
Note
399(1)
Further Reading
399(2)
About The Author 401(2)
Index 403
JEAN PAUL ISSON is a recognized worldwide expert and evangelist in Big Data Analytics and Advanced Business Analytics, with over 22 years of experience. He is the author of Win with Advanced Business Analytics and People Analytics in the Era of Big Data.

As Global Vice President of Predictive Analytics & BI at Monster Worldwide Inc. he has built his team from the ground up and successfully conceived and implemented global customer scoring, predictive models and segmentation, machine learning and deep learning solutions, web mining applications, and people analytics solutions for Monster across North America, Europe, and Asia/Pacific. He is also the Founder of the People Analytics Institute.