WHITE PAPER:
Many organizations have reconsidered their commitments to data modeling in the face of NoSQL and big data systems, as well as XML information management. However, should you really be shifting focus away from data modeling?
WHITE PAPER:
This white paper discusses: What is an industry model? What is the value of industry models? Considerations for building or buying data models IBM Industry Models—business and technical blueprints Reducing time to value with IBM Industry Models
WHITE PAPER:
Uncertainty makes strategic planning complex. Removing uncertainty can create unlimited business value. There are solutions to help organizations overcome uncertainty and achieve results. Read this white paper to learn how to drive strategic planning with predictive modeling.
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:
Read on to find details about SAPs BusinessObjects Predictive Analysis, including how the NBA used HANA to help cater to stat-hungry fans.
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:
This paper explains how modeling information architecture (IA) can help reduce the costs associated with data management. Read this now and learn about the benefits of implementing IA and how Sybase's option offers modeling support for database design and enterprise architecture.
WHITE PAPER:
This white paper describes how IBM's Information Server FastTrack accelerates the translation of business requirements into data integration projects. Data integration projects require collaboration across analysts, data modelers and developers.
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.