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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.
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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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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?
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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.
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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.
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By using the Oracle Exadata Database Machine as a data warehouse platform you have a balanced, high performance hardware configuration. This paper focuses on the other two corner stones, data modeling and data loading, providing a set of best practices and examples for deploying a data warehouse on the Oracle Exadata Database Machine.
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Whether or not analytics should become an integral part of an organization’s planning and decision-making seems to be beyond question However, at what level, for what purpose and how to go about deploying analytics are questions that each organization needs to answer for itself. These questions are the focus of this paper.
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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.