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Data Models

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Data Models Reports
 
How to Operationalize Machine Learning and Data Science Projects
sponsored by IBM
ANALYST REPORT: Companies everywhere are relying on data science to solve business problems. However, many data scientists and engineers lack the skills to successfully operationalize data science models. Read this research report to learn how your organization can successfully operationalize machine learning and data science projects.
Posted: 12 Nov 2018 | Published: 12 Nov 2018

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

The Big Data Surge: Data Modeling Challenges & Best Practices for Prepping Big Data Apps for Production
sponsored by IBM
EGUIDE: Surging big data is changing data modeling techniques and app development cycles. Read on to discover what you should expect from big data's near-future and best practices when it comes to transitioning big data applications into the production stage.
Posted: 27 Jul 2016 | Published: 26 Jul 2016

IBM

Utilizing Data-aware Storage in the Age of Convergence
sponsored by IBM
EGUIDE: Access the latest on converged, data-aware storage architectures, which seek to improve performance optimization through smart deduplication and compression schemes, app-aligned caching and tiering, policy-definable QoS, and data protection schemes. Additionally, discover why flash is crucial to convergence.
Posted: 03 Nov 2016 | Published: 27 Oct 2016

IBM

Applying Business Analytics Webinar Series - Got Bad Data? Part 3
sponsored by SAS
WEBCAST: Tune in to this Webinar to find out how data quality influences the effectiveness of predictive analytics and forecasting. You’ll learn how to go beyond name and address matching to realize the potential of numerical data quality, how to overcome insufficient yet relevant data from your predictive and forecasting models, and more.
Posted: 09 Apr 2010 | Premiered: Apr 9, 2010

SAS

Fast-Tracking Data Warehousing & BI Projects via Intelligent Data Modeling
sponsored by Embarcadero Technologies, Inc.
WHITE PAPER: 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.
Posted: 26 Jan 2012 | Published: 19 Jan 2012

Embarcadero Technologies, Inc.

Presentation Transcript: Databases - When it pays to invest
sponsored by Oracle Corporation
PRESENTATION TRANSCRIPT: In today's economic environment, it is imperative that companies begin addressing ways to manage all information assets in an integrated, holistic way. Philip Howard, Research Director for Bloor Research, and Chris Baker, Senior Vice President at Oracle, discuss best practices for obtaining a fully integrated Enterprise Data Management platform.
Posted: 13 Feb 2009 | Published: 13 Feb 2009

Oracle Corporation

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: 20 Apr 2011 | Published: 20 Apr 2011

CA ERwin from CA Technologies

ERwin® in the Cloud: How Data Modeling Supports Database as a Service (DaaS) Implementations
sponsored by CA ERwin from CA Technologies
WHITE PAPER: Learn how Data Modeling supports cloud computing since interaction among the Cloud Service Provider, Cloud Administration and Customer needs to include a well thought out data architecture before a DBMS designed offering in cloud computing is deployed. Continue reading to learn more.
Posted: 19 Oct 2010 | Published: 01 Jun 2010

CA ERwin from CA Technologies
 

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