April 2012

Sponsored by International Business Machines Corp

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In this paper, we describe what operational analytics is and what it offers to the business. We explore its relationship to business intelligence (BI) and see how traditional data warehouse architectures struggle to support it. Now, the combination of advanced hardware and software technologies–as seen in the IBM DB2 Analytics Accelerator, combining IBM Netezza with System z–provide the opportunity to create a new integrated platform delivering powerful operational analytics within the existing IT fabric of the enterprise. 

Abstract

Business is running ever faster–generating, collecting and using increasing volumes of data about every aspect of the interactions between suppliers, manufacturers, retailers and customers. Within these mountains of data are seams of gold–patterns of behavior that can be interpreted, classified and analyzed to allow predictions of real value. Which treatment is likely to be most effective for this patient? What can we offer that this particular customer is more likely to buy? Can we identify if that transaction is fraudulent before the sale is closed?

To these questions and more, operational analytics–the combination of deep data analysis and transaction processing systems–has an answer.

This paper describes what operational analytics is and what it offers to the business. We explore its relationship to business intelligence (BI) and see how traditional data warehouse architectures struggle to support it. Now, the combination of advanced hardware and software technologies provide the opportunity to create a new integrated platform delivering powerful operational analytics within the existing IT fabric of the enterprise.

With the IBM DB2 Analytics Accelerator, a new hardware/software offering on System z, the power of the massively parallel processing (MPP) IBM Netezza is closely integrated with the mainframe and accessed directly and transparently via DB2 on z/OS. The IBM DB2 Analytics Accelerator brings enormous query performance gains to analytic queries and enables direct integration with operational processes.

This integrated environment also enables distributed data marts to be re-turned to the mainframe environment, enabling significant reductions in data management and total ownership costs.