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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.
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Despite criticism of application development methodology over the years, some fundamental problems haven’t been addressed successfully. This paper examines a new direction supported by the IBM InfoSphere Foundation Tools. These tools provide a coordinated approach well-suited to the special needs of contemporary information-centric development.
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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.
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.
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Learn how Data Modeling supports cloud computing since interaction among the Cloud Service Provider, Cloud Administration and Customer needs to include a well thought out data architecture before a DBMS designed offering in cloud computing is deployed. Continue reading to learn more.
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:
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 paper outlines an information architecture (IA) and why it is useful in determining everything from the robustness of IT projects to testing business process scenarios to see if they satisfy the wide-ranging needs of your business. Read this now to learn more about IA, including its basic design, how to start your program and more.
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Enterprise data is largely falling short of a standard that makes it possible to utilize in how business will be conducted in the next decade. Most enterprise data is “adequate” for basic operational needs today. Download this paper to learn how to get the most out of your enterprise data.
