Information Resources
Analyst Reports
The Total Economic Impact Of IBM's Netezza Data Warehouse Appliance With Advanced Analytics - A Forrester Total Economic Impact™ Study Prepared For IBM
In June 2011, IBM commissioned Forrester Consulting to examine the total economic impact and potential return on investment (ROI) enterprises may realize by deploying its Netezza data warehouse appliance with advanced analytics. The purpose of this study is to provide readers with a framework to evaluate the potential financial impact of the IBM Netezza appliance on their organizations.
IBM Netezza Data Warehouse Appliances Provide Competitive Differentiation Through Faster Analytics While Reducing Capital And Operational Costs
Our interviews with one existing customer, Epsilon, a multichannel marketing services provider, and subsequent financial analysis based on assumptions that Forrester used illustrate the potential ROI from the use of IBM Netezza appliances. Epsilon is one of IBM Netezza's largest partners in the campaign marketing industry.
Bloor - Netezza Data Virtualizer Powered by Composite Software
It is often the case in large enterprises that multiple data marts are deployed, along with a central enterprise data warehouse acting as a system of record. While these data marts serve the requirements of the departments or divisions that implement them, a frequent requirement is to merge data across these implementations.
Bloor - Netezza: Enabling Advanced Analytics
In-place analytics processing will mean that network bottlenecks can be eliminated, while the high performance processing that Netezza is renowned for should deliver significantly faster time to insight.
EMA - Netezza Extends TwinFin™ Appliance Functionality with Availability of SAS/ACCESS Engine Integration
EMA covers the capabilities of the TwinFin™ data warehouse and analytics appliance platform through its partnership with SAS® by integrating the SAS/ACCESS® Engine. The report positions Netezza as solid alternative to traditional data warehouse solutions by bundling storage, processing, database functions and analytics into a single integrated system.
