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Comparing the Cost of Business Intelligence - Proprietary Versus Open Source by Pentaho Corporation
July 13, 2010 - (Free Research) This webcast will detail a new analyst report, Lowering the Cost of Business Intelligence with Open Source which compares the software and support costs of traditional BI vendors such as IBM, Oracle and SAP with commercial open source BI from Pentaho.
Open Source Master Data Management - The Time is Right by Talend
March 16, 2010 - (Free Research) Proper master data management (MDM) is very valuable when available to enterprise business processes and analytics. However, master data projects are often challenging, architecturally complex, time intensive and expensive. This paper explains why the time is right for open source MDM, and predicts the effects of open source on the MDM marketplace.
Moving Open Source Integration Infrastructure into Production by Progress FUSE
June 2010 - (Free Research) In this webinar hear how MyShape, a popular retail e-commerce site conducted the evaluation stage as well as the deployment of open source infrastructure and why their choice to use Apache ActiveMQ, Camel and FUSE led to the success of their business.
The Role of Open Source Data Integration - An Analyst White Paper, by Mark Madsen by Talend
January 2009 - (Free Research) This report by Mark Madsen will explain what data integration is, and especially the difference between Operational Data Integration and Analytic Data Integration. It highlights the benefits of open source for data integration, and provides a series of recommendations to make the integration job easier, repeatable and more productive.
Virtualizing AMD-Powered HP ProLiant servers using Open Source Hypervisor KVM by Red Hat, HP, and AMD
May 2010 - (Free Research) In this webcast, discover the advantages and disadvantages of various methods for virtualizing an x86 architecture. Find out about binary translation, paravirtualization, KVM, and hardware assisted virtualization to determine how each approach can be used to aid in the traditionally complex process of virtualizing x86 architectures.
Master Data Management Projects in Practice - An Information Difference Research Study by Talend
December 2009 - (Free Research) Organizations are often turning to Master Data Management as a key enabler in improving the timeliness, quality and reliability of BI with the ultimate goal of improving business performance. This survey report presents recommendations on the "do and don't" of MDM as well as some findings on the use of open source and manual coding in MDM projects.
Wisdom of Crowds Business Intelligence Market Study: Project Findings and Analysis Report by Pentaho Corporation
June 2010 - (Free Research) The "Wisdom of Crowds", a Business Intelligence Market Study, was created to give a voice to those using BI solutions, creating a new and different perspective for measuring BI vendors and products in the market. The study was opened for input to any valid users with first-hand BI vendor and product experience. Read this report to learn more.
Working Smarter By Moving To IBM/RedHat Based Desktop Software Alternatives by IBM
August 2009 - (Free Research) This webcast provides practical insights on winning over business end users by overcoming their perceptions and knowledge gaps around Linux desktops and smarter collaboration capabilities that can help people make better decisions faster for greater productivity and business agility.
E-Guide: Expert Guide to POWER7 Unix Servers Features and Functionality by Mainline Information Systems
May 2010 - (Free Research) Big industry players are not counting Unix out just yet and have recently launched new products aimed at this market. This expert E-Guide from SearchDataCenter.com and Mainline, reviews IBM's recent roll out of its multicore POWER7 servers.
High Performance for Integrating Massive Data Volumes with Talend Integration Suite MP by Talend
March 2010 - (Free Research) Processing very large data sets provides unique constraints, especially when time windows available for this processing are shrinking. This paper presents a variety of technologies available to accelerate the processing of large data volumes, including massive parallelization, optimized data-set-mode processing, grid deployment, and load balancing.
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