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Private cloud delivery model for supplying centralized analytics services

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1 Author(s)
Yarter, L. C. ; IBM Chief Information Office, Maryland, NY, USA

Business analytics has become vital for businesses to achieve their near-term and strategic goals. Historically, large enterprises have used a decentralized information technology delivery model to meet reporting and analytics needs within each business unit. Rising demand for analytics, combined with the cost of decentralized delivery, has driven businesses to look at alternative delivery patterns. Chief information officers (CIOs) have a renewed interest in considering centralized, virtualized services—given their desire to reduce expenses without reduced business flexibility. The Chief Information Office of IBM has pioneered a private cloud delivery model for delivering analytics tooling to internal users (IBM employees), providing centralization and standardization of service. Through evaluation of analytics usage patterns, IBM developed a common analytics services strategy to reduce expenses and solution deployment time while improving business agility and insights. IBM deployed a share-all private cloud model (in which users deploy reports on the same instance of the hardware and software) on an extensible Linux® on the IBM System z® infrastructure to deliver ubiquitous analytics service to every business process area. The IBM software-as-a-service analytics delivery model allowed its more than 190,000 business users to maintain user or user-group solution autonomy while providing access to cost-effective ($25 million savings over five years), timely commodity services.

Note: The Institute of Electrical and Electronics Engineers, Incorporated is distributing this Article with permission of the International Business Machines Corporation (IBM) who is the exclusive owner. The recipient of this Article may not assign, sublicense, lease, rent or otherwise transfer, reproduce, prepare derivative works, publicly display or perform, or distribute the Article.  

Published in:

IBM Journal of Research and Development  (Volume:56 ,  Issue: 6 )

Date of Publication:

Nov.-Dec. 2012

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