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BIG DATA APPLIANCES FOR IN-MEMORY COMPUTING - WRANGLE YOUR DATA





BIG DATA APPLIANCES FOR IN-MEMORY COMPUTING - WRANGLE YOUR DATA
Ganapathi Pulipaka has received rave reviews for his book. "The business intelligence analytics of any organization must determine the usage of big data tools keeping in sight of the pain points in the enterprise. This solution should address all the challenges related to structured and unstructured data in the enterprise and on the scattered footprint of the technical landscape of the company. Improper change management and release management in the company could result in information silos in the enterprise. Organizations need to define their enterprise strategy for structured and unstructured data as part of the strategic objectives of the company. This book provided valuable insights into leveraging predictive analytics to run your business and make smarter decisionsthat are critical to the success as a direct result of having the proper, accurate, and EFFECTIVE reporting."

- Tammy Amirault, Vice President - SAP Management Consulting & ERP, Prosum Technology Services, one of the most respected industry voices of SAP, who led large scale SAP global projects internationally for Fortune 100 corporations including a bevy of SAP BW analytics projects with a budget in excess of $110M for global rollouts.

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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.
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