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Data Models

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Data Models White Papers (View All Report Types)
 
Understanding Data Streams in IoT
sponsored by SAS
WHITE PAPER: View this forward-thinking resource and discover a strategy that allows you to quickly decipher and analyze volumes of continuously flowing events held in streams of data, instead of having to run queries against stored data alone.
Posted: 07 Apr 2016 | Published: 07 Apr 2016

SAS

Redefine Your Analytics Journey With Self-Service Data Discovery and Interactive Predictive Analytics
sponsored by SAS
WHITE PAPER: This white paper explores how you can obtain self-service, interactive analytics software that can be used whenever and wherever you want. Read on to implement the kind of analytics that keeps pace with the rapidly changing business world.
Posted: 06 Jan 2016 | Published: 06 Jan 2016

SAS

Advance Enterprise Analytics with Self-Service and Governance
sponsored by Pyramid Analytics
WHITE PAPER: Self-service BI can help business users quickly create data models and enable better decision-making, but this can't be achieved without centralized, managed security. Discover a highly scalable BI platform that can balance self-service BI with complete governance.
Posted: 19 May 2016 | Published: 19 May 2016

Pyramid Analytics

Fast-Tracking Data Warehousing & Business Intelligence Projects via Intelligent Data Modeling
sponsored by Embarcadero Technologies, Inc.
WHITE PAPER: 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.
Posted: 15 Jun 2011 | Published: 01 Jan 2010

Embarcadero Technologies, Inc.

Accelerating Application Deployment with InfoSphere Foundation Tools
sponsored by IBM
WHITE PAPER: Despite criticism of application development methodology over the years, some fundamental problems haven’t been addressed successfully. This paper examines a new direction supported by the IBM InfoSphere Foundation Tools. These tools provide a coordinated approach well-suited to the special needs of contemporary information-centric development.
Posted: 16 Aug 2010 | Published: 13 Aug 2010

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

Driving Strategic Planning with Predictive Modeling
sponsored by Oracle Corporation
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.
Posted: 18 May 2010 | Published: 18 Jul 2008

Oracle Corporation

Scaling SOA through EAI Enhancement and Use of Model-based Standards
sponsored by Progress
WHITE PAPER: This white paper details how to enhance an EAI environment and enable SOA while improving productivity, reducing manual governance, and optimizing performance.
Posted: 19 Feb 2007 | Published: 01 Feb 2007

Progress

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

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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