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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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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.
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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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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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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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This paper highlights the performance and scalability potential of InfoSphere DataStage 8.1 based on a benchmark test simulating a data warehouse scenario. The benchmark is designed to use the profiled situation to provide insight about how InfoSphere DataStage addresses customers' key FAQs when designing their information integration architecture.
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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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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.
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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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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.
