WHITE PAPER:
This paper analyzes the issues of conventional data warehouse design process and explains how this practice can be improved using a business-model-driven process in support of effective Business Intelligence.
TRIAL SOFTWARE:
IBM InfoSphere Data Architect is a collaborative data design solution to help you discover, model, relate, and standardize diverse and distributed data assets. It supports dimensional modeling. This page contains more information about the product and access to a 30-day trial.
WHITE PAPER:
Discover how a private technical compute cloud can help your business provide access to remote, full 3D technical visualization and rendering capabilities that can help to enhance collaboration and productivity.
EGUIDE:
In this e-guide, gain essential knowledge of recent developments around IT services. Read on to learn why success entails more than delivering snazzy services, and why enterprise architects are working to bring SOA and master data management (MDM) efforts together.
WHITE PAPER:
Read this white paper and learn how the data warehouse, metadata and modeling environment will be transformed in the next few years — and what you need to do to leverage it for your business, the major components of DW 2.0 architectures, and key modeling and metadata management strategies for DW 2.0.
WHITE PAPER:
The construction of a data model is one of the more difficult tasks of software engineering and is often pivotal to the success or failure of a project. Many factors determine the effectiveness of a data model. In this white paper, industry expert Michael Blaha covers the Top 10 pitfalls to avoid - from both the strategy and detail perspective.
WHITE PAPER:
Through data modeling of BI systems, we can meet many of today’s data challenges. Through logical and physical modeling of business intelligence systems, we can enable the delivery of the correct business information to business users. Read this paper to learn more.
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.
WHITE PAPER:
The key enterprise risk management (ERM) issue for many financial institutions is to get enriched data in a single place in order to report on it. Learn best practices for data management that are critical for ERM.
WHITE PAPER:
Read on to find details about SAPs BusinessObjects Predictive Analysis, including how the NBA used HANA to help cater to stat-hungry fans.
