Big Data Appliances for In-Memory Computing : A Real-World Research Guide for Corporations to Tame and Wrangle Their Data
Language: English
Published by High Performance Computing Institute Of Technology Dez 2015, 2015
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Neuware - This book is a scientific expedition to research and explore the enterprise-grade big data appliances with blended OLTP and OLAP capabilities. Enterprise database systems with the aid of big data analytics create an intelligent ecosystem by taming and wrangling the data coming from extreme-disparate sources of structured and unstructured channels with massive parallelization techniques to discover, visualize, predict, and action the patterns and trends of mashups of big data. The book delves deeper into the research results of industry relevant case studies with the disruption of in-memory computing platform innovation that diffuses high-speed computing and dynamic performance for business applications and explores how these modern big data analytics tools shape the future of aerospace, automotive, consumer goods and beverages, healthcare, government services, high tech, and public sector industries.
Seller Inventory # 9780692599570
- Title
- Big Data Appliances for In-Memory Computing : A Real-World Research Guide for Corporations to Tame and Wrangle Their Data
- Author
- Ganapathi Pulipaka
- Publisher
- High Performance Computing Institute Of Technology Dez 2015
- Publication year
- 2015
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0692599576
- ISBN 13
- 9780692599570
- Item weight
- 290 grams
- Dimensions
- 229x152x11 mm
This book is a scientific expedition to research and explore the enterprise-grade big data appliances with blended OLTP and OLAP capabilities. Enterprise database systems with the aid of big data analytics create an intelligent ecosystem by taming and wrangling the data coming from extreme-disparate sources of structured and unstructured channels with massive parallelization techniques to discover, visualize, predict, and action the patterns and trends of mashups of big data. The book delves deeper into the research results of industry relevant case studies with the disruption of in-memory computing platform innovation that diffuses high-speed computing and dynamic performance for business applications and explores how these modern big data analytics tools shape the future of aerospace, automotive, consumer goods and beverages, healthcare, government services, high tech, and public sector industries.
"Synopsis" may belong to another edition of this title.
About the Author
Academia
Ganapathi Pulipaka is research scholar in Computer and Information Systems who holds a Professional Doctorate Degree in Information Systems and Enterprise Resource Management from California Intercontinental University, Irvine, CA. His previous academic work includes a doctoral dissertation "SAP HANA and In-Memory Computing to Resolve Biggest Business Conundrums," and more than 200 research papers on a bevy of research topics such as modern databases, technology innovation, and strategic management. He is a popularizer of science and technologies.
Professional Background
Ganapathi Pulipaka is a distinguished technology leader providing innovatory solution architecture on SAP Business systems, Enterprise application development design engineering, management, and consulting delivery services offers expertise in SAP delivery execution and executive interaction as a trusted advisor. He started his career as an SAP ABAP Programmer. He has implemented around 25 SAP projects for Fortune 100 corporations and various other clients in the past 17+ years on next-generation SAP Applications providing a comprehensive portfolio of consulting solutions. He worked for 21 global corporations implementing SAP projects in building Global COE for SAP ERP, HANA, CRM, SRM, SCM, PLM, PPM, and BW Netweaver products. Ganapathi Pulipaka is an SAP Certified Professional.
"About the title" may belong to another edition of this title.
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