Modeling White Papers

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Oracle Business Intelligence Standard One Edition
sponsored by Oracle Corporation
WHITE PAPER: This white paper discusses Oracle Business Intelligence Standard Edition One, a powerful, integrated and comprehensive business intelligence system. Learn how to provide business insight, value, and ease of use for both, end users and administrators.
Posted: 04 Dec 2007 | Published: 03 Dec 2007

Oracle Corporation

Ten Things to Avoid in a Data Model
sponsored by CA ERwin from CA Technologies
WHITE PAPER: 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.
Posted: 19 Oct 2010 | Published: 01 Aug 2010

CA ERwin from CA Technologies

Best Practices for Implementing a Data Warehouse on Oracle Exadata Database Machine
sponsored by Oracle Corporation
WHITE PAPER: 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.
Posted: 12 Mar 2012 | Published: 30 Sep 2010

Oracle Corporation

Best Practices for Implementing a Data Warehouse on Oracle Exadata Database Machine
sponsored by Oracle Corporation
WHITE PAPER: 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.
Posted: 25 Apr 2011 | Published: 30 Nov 2010

Oracle Corporation

Data Visualization: 7 Considerations for Visualization Deployment
sponsored by SAS
WHITE PAPER: 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.
Posted: 05 May 2014 | Published: 28 Apr 2014

SAS

Business-Model-Driven Data Warehousing: Keeping Data Warehouses Connected to Your Business
sponsored by Kalido
WHITE PAPER: 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.
Posted: 04 Jun 2008 | Published: 01 Jun 2008

Kalido

Improving Data Quality Through Data Modeling
sponsored by CA ERwin from CA Technologies
WHITE PAPER: 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.
Posted: 20 Apr 2011 | Published: 20 Apr 2011

CA ERwin from CA Technologies

The Benefits of Data Modeling in Business Intelligence
sponsored by CA ERwin from CA Technologies
WHITE PAPER: 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.
Posted: 08 Jun 2010 | Published: 30 Oct 2009

CA ERwin from CA Technologies

Choosing visual properties for successful visualizations
sponsored by IBM
WHITE PAPER: In the following article, IBM experts address a key aspect in the design process.
Posted: 09 Oct 2013 | Published: 09 Oct 2013

IBM

IBM Information Server FastTrack
sponsored by IBM
WHITE PAPER: 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.
Posted: 13 Aug 2008 | Published: 13 Aug 2008

IBM