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Leaders and Innovators: How Data-Driven Organizations Are Winnin
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所在地：NY, 美國
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估計於 6月17日, 一至 6月22日, 六之間送達 運送地點 43230
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- Title
- Leaders and Innovators: How Data-Driven Organizations Are Winnin
- ISBN
- 9781119232575
- Subject Area
- Computers, Business & Economics
- Publication Name
- Leaders and Innovators : How Data-Driven Organizations Are Winning with Analytics
- Item Length
- 9 in
- Publisher
- Wiley & Sons, Incorporated, John
- Subject
- Mathematical & Statistical Software, Decision-Making & Problem Solving, Databases / General
- Publication Year
- 2016
- Series
- Wiley and Sas Business Ser.
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 1 in
- Item Width
- 5.9 in
- Item Weight
- 13.6 Oz
- Number of Pages
- 240 Pages
關於產品
Product Information
An integrated, strategic approach to higher-value analytics Leaders and Innovators: How Data-Driven Organizations Are Winning with Analytics shows how businesses leverage enterprise analytics to gain strategic insights for profitability and growth.
Product Identifiers
Publisher
Wiley & Sons, Incorporated, John
ISBN-10
1119232570
ISBN-13
9781119232575
eBay Product ID (ePID)
220285262
Product Key Features
Publication Name
Leaders and Innovators : How Data-Driven Organizations Are Winning with Analytics
Format
Hardcover
Language
English
Subject
Mathematical & Statistical Software, Decision-Making & Problem Solving, Databases / General
Publication Year
2016
Series
Wiley and Sas Business Ser.
Type
Textbook
Subject Area
Computers, Business & Economics
Number of Pages
240 Pages
Dimensions
Item Length
9 in
Item Height
1 in
Item Width
5.9 in
Item Weight
13.6 Oz
Additional Product Features
LCCN
2016-021571
Intended Audience
Trade
Lc Classification Number
Qa76.9.I52n48 2016
Reviews
"Data management and analytics to beat your competitors; full of examples and case studies of big data wins" The Magpi, issue 60, Aug 2017
Table of Content
Foreword xi Acknowledgments xv About the Author xvii Introduction xix Chapter 1 The Analytical Data Life Cycle 1 Stage 1: Data Exploration 2 Stage 2: Data Preparation 3 Stage 3: Model Development 4 Stage 4: Model Deployment 6 End-to-End Process 8 Chapter 2 In-Database Processing 11 Background 12 Traditional Approach 13 In-Database Approach 15 The Need for In-Database Analytics 16 Success Stories and Use Cases 18 In-Database Data Quality 35 Investment for In-Database Processing 44 Endnotes 47 Chapter 3 In-Memory Analytics 49 Background 50 Traditional Approach 51 In-Memory Analytics Approach 53 The Need for In-Memory Analytics 56 Success Stories and Use Cases 65 Investment for In-Memory Analytics 80 Chapter 4 Hadoop 83 Background 84 Hadoop in the Big Data Environment 86 Use Cases for Hadoop 87 Hadoop Architecture 89 Best Practices 92 Benefits of Hadoop 95 Use Cases and Success Stories 97 A Collection of Use Cases 103 Endnote 105 Chapter 5 Bringing It All Together 107 Background 108 Collaborative Data Architecture 109 Scenarios for the Collaborative Data Architecture 113 How In-Database, In-Memory, and Hadoop Are Complementary in a Collaborative Data Architecture 119 Use Cases and Customer Success Stories 122 Investment and Costs 150 Endnotes 151 Chapter 6 Final Thoughts and Conclusion 153 Five Focus Areas 154 Cloud Computing 157 Security: Cyber, Data Breach 168 Automating Prescriptive Analytics: IoT, Events, and Data Streams 179 Cognitive Analytics 188 Anything as a Service (XaaS) 197 Conclusion 204 Afterword 208 Index 210
Copyright Date
2016
Afterword by
Franks, Bill
Dewey Decimal
001.4226
Dewey Edition
23
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