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