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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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The following Harvard Business Review report explores the current state of data visualisation. Hear from many leading authors on how to leverage data visualisation, and the right times to use it.
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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.
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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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In this white paper, discover a rapid-deployment technology for mobile analytics visualization, so you can take full advantage of data visualization capabilities anywhere, at any time. Explore the benefits you'll get with rapid-deployment, and learn how easy it is to get a mobile analytics strategy up and running within two weeks.
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The following white paper explores the top 7 considerations for implementing a data visualization solution in your enterprise. Learn how data visualization can give way to far deeper insights, better decision making, and much more.
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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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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 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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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.
