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frictionless discovery

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Published By: IBM     Published Date: Jan 27, 2017
In todayís highly distributed, multi-platform world, the data needed to solve any particular decision making need is increasingly likely to be found across a wide variety of sources. As a result, traditional manual approaches requiring prior collection, storage and integration of extensive sets of data in the analystís preferred exploration environment are becoming less useful. Data virtualization, which offers transparent access to distributed, diverse data sources, offers a valuable alternative approach in these circumstances.
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IBM
Published By: Pentaho     Published Date: Apr 28, 2016
Today, the need for self-service data discovery is making data governance a charged topic. As business-driven data discovery emerges as a fundamental need, the ability to ensure that data and analytics are trustworthy and protected becomes both more difficult and more imperative. This research explains how to manage the barriers and risks of self-service and enable agile data discovery across the organization by extending existing data governance framework concepts to the data-driven and discovery-oriented business. Youíll learn: - The implications of the "freedom vs. control" paradox - How to design for iterative, "frictionless" discovery - Critical checkpoints in data discovery process where governance should be in place
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pentaho, governed data, data and analytics, governance framework, freedom vs control, frictionless discovery, networking, it management, wireless, enterprise applications, data management
    
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