Vivek Kale

Big Data Computing (eBook, PDF)

A Guide for Business and Technology Managers

• Format: PDF

Produktbeschreibung

This book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It provides a framework that enables business and technical managers to make optimal decisions necessary for the successful migration to Big Data computing environments and applications within their organizations.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 530
• Erscheinungstermin: 25. November 2016
• Englisch
• ISBN-13: 9781498715348
• Artikelnr.: 47382518

Autorenporträt

Vivek Kale has more than two decades of professional IT experience during which he has handled and consulted on various aspects of enterprise-wide information modeling, enterprise architectures, business process redesign, and e-business architectures. He has been Group CIO of Essar Group, the steel/oil and gas major of India, as well as Raymond Ltd., the textile and apparel major of India. He is a seasoned practitioner in transforming the business of IT, facilitating business agility and enhancing IT-enabled enterprise intelligence. He is the author of Implementing SAP R/3: The Guide for Business and Technology Managers (Sams 2000) and Guide to Cloud Computing for Business and Technology Managers: From Distributed Computing to Cloudware Applications (CRC Press 2015).

Inhaltsangabe

Preface. Acknowledgements. Patterns in Data Deluge. Genesis of Big Data
Computing. Database Basics. Text Mining Basics. Road to Big Data Computing.
Data Warehouse Basics. Data Mining Basics. Analytics Basics. Cloud
Computing Basics. Big Data Computing. Big Data. Multimedia Big Data. Big
Data Technologies. Big Data Vendors. Big Data Development with Hadoop. Big
Data Implementation. Big Data Computing Applications. Web Applications.
Social Network Applications. Mobile Applications. Real-Time Data
Applications. Context-Aware Applications. Epilogue. Appendix. References.
Index.