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Enterprise Modeling

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Enterprise Modeling White Papers (View All Report Types)
 
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

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

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

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

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

Noetix: Getting Analytics to Business Users in an Oracle Applications Environment
sponsored by Noetix Corporation
WHITE PAPER: This IDC Vendor Profile highlights the solution offerings and market strategy of Noetix, a business intelligence software vendor.
Posted: 20 Jun 2008 | Published: 01 May 2007

Noetix Corporation

Information-led Transformation Planning, Modeling and Building New Intelligence Applications
sponsored by IBM
WHITE PAPER: 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
Posted: 24 Mar 2011 | Published: 24 Mar 2011

IBM

Rapid-deployment Solution for Mobile Analytics Visualization
sponsored by Hewlett-Packard Enterprise
WHITE PAPER: 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.
Posted: 24 Feb 2014 | Published: 31 Oct 2013

Hewlett-Packard Enterprise

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: 20 Apr 2011 | Published: 20 Apr 2011

CA ERwin from CA Technologies

Top 10 Data Mining Mistakes
sponsored by SAS
WHITE PAPER: 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.
Posted: 07 Apr 2010 | Published: 07 Apr 2010

SAS
 
 
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