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Read this paper to learn all the factors you need to consider when choosing a data modeling tool. You will learn about the different model types and how each tool measures up to the demanding needs of your company today and in the future. This paper will lay out all the information you need to make a clear decision on data modeling today.
WHITE PAPER:
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 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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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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Read on to find details about SAPs BusinessObjects Predictive Analysis, including how the NBA used HANA to help cater to stat-hungry fans.
WHITE PAPER:
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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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
WHITE PAPER:
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.
