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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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Often times Business Intelligence (BI) projects miss the mark with their business users because the proper documenting of required data and related business rules is not executed. This paper looks at fast-tracking data warehousing and BI projects using 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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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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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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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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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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This paper examines the business issues that drive organizations to consider a real-time change data capture solution to optimize ETL processes. This helps alleviate batch windows to enable the delivery of timely, trusted information to the business.
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In this white paper, you will learn intelligent data modeling practices to design and deliver superior business intelligence (BI) faster, the characteristics and benefits of intelligent data modeling and how to promote the use of data models to fast-track data warehouse and BI projects.
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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.
