WHITE PAPER:
NoetixViews transforms the complexity of the Oracle E-Business Suite database into recognizable business views of data that are used to create operational reports and ad hoc queries. NoetixViews enables faster, easier and more cost-effective access to information stored in the Oracle E-Business Suite data structure. Read this paper to learn more.
WHITE PAPER:
Data warehouse appliances have transformed the DW with a platform designed to deliver optimal price and performance with extreme simplicity. This paper outlines the IBM Netezza data warehouse appliance and how it offers extreme time to value, agility and ability to grow with new workloads, cost reduction of ongoing maintenance and more.
WHITE PAPER:
Visual analytics is the process of analytical reasoning facilitated by interactive visual interfaces. Its becoming the fastest way for people to explore and understand Business Intelligence data of any size. This paper will introduce you to the seven essential elements of true visual analytics applications.
WHITE PAPER:
This white paper highlights how organizations can leverage big data to solve business challenges. It focuses on query-able data warehouses as a way to reduce costs and gain business insights. Discover how you can free up your data warehouse from processes slowing it down and disrupting revenue goals.
WHITE PAPER:
In large networks, the sheer number of permission settings makes it almost impossible to gain a clear overview of overall security, and checking that all those permission are in compliance with corporate and regulatory standards is a Herculean task.
WHITE PAPER:
Read this white paper and learn about the intelligent software in the Oracle Exadata Storage Server that accelerates database query processing (DQP) by offloading database query processing to the storage layer.
WHITE PAPER:
This white paper focuses on the use of a log-based, real-time change data capture (CDC) solution to enable real-time reporting using a low overhead solution that minimizes the impact on IT infrastructure.
WHITE PAPER:
In the following paper, we briefly describe, and illustrate from examples, what we believe are the “Top 10” mistakes of data mining, in terms of frequency and seriousness. Most are basic, though a few are subtle. All have, when undetected, left analysts worse off than if they’d never looked at their data.
