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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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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:
Sybase IQ is a market-leading analytics server which enables organizations to perform deep analysis of massive amounts of data, accessed by multiple users requiring answers in real time.
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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.
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At the core of any BI should be the ability to align business needs with the data infrastructure supporting them. This is almost impossible to do without a data model. Yet many BI implementers do not understand the need for these design components. This paper will examine the major benefits that data models have on BI environments.
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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.
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Read on to find details about SAPs BusinessObjects Predictive Analysis, including how the NBA used HANA to help cater to stat-hungry fans.
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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
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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.
