Big data war : how to survive global big data competition /
Gorde:
| Egile nagusia: | |
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| Formatua: | Baliabide elektronikoa eBook |
| Hizkuntza: | ingelesa |
| Argitaratua: |
New York, New York (222 East 46th Street, New York, NY 10017) :
Business Expert Press,
2016.
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| Edizioa: | First edition. |
| Saila: | Big data and business analytics collection.
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| Gaiak: | |
| Sarrera elektronikoa: | An electronic book accessible through the World Wide Web; click to view |
| Etiketak: |
Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!
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| Laburpena: | Written by Patrick H. Park, an author of Brain Work (Korea, 2014). The book mainly focuses on why data analytics fails in business. It provides an objective analysis and root causes of the phenomenon, instead of abstract criticism of utility of data analytics. The author, then, explains in detail on how companies can survive and win the global big data competition, based on actual cases of companies. Having established the execution and performance-oriented big data methodology based on over 10 years of experience in the field as an authority in big data strategy, the author identifies core principles of data analytics using case analysis of failures and successes of actual companies. Moreover, he endeavors to share with readers the principles regarding how innovative global companies became successful through utilization of big data. This book is a quintessential big data analytics, in which the author's know-how from direct and indirect experiences is condensed. How do we survive at this big data war in which Facebook in SNS, Amazon in e-commerce, and Google in search expand their platforms to other areas based on their respective distinct markets? The answer can be found in this book. |
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| Alearen deskribapena: | Includes index. |
| Deskribapen fisikoa: | 1 online resource (x, 195 pages) Also available in print. |
| Formatua: | Mode of access: World Wide Web. System requirements: Adobe Acrobat reader. |
| ISBN: | 9781631575617 |
| ISSN: | 2333-6757 |
| Sartu: | Access restricted to authorized users and institutions. |