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	<title>Comments on: 7 myths about open sourcing your company&#8217;s software &#124; Opensource.com</title>
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	<link>https://www.epanorama.net/blog/2017/05/07/7-myths-about-open-sourcing-your-companys-software-opensource-com/</link>
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		<title>By: Tomi Engdahl</title>
		<link>https://www.epanorama.net/blog/2017/05/07/7-myths-about-open-sourcing-your-companys-software-opensource-com/comment-page-1/#comment-1546691</link>
		<dc:creator><![CDATA[Tomi Engdahl]]></dc:creator>
		<pubDate>Fri, 12 May 2017 12:49:54 +0000</pubDate>
		<guid isPermaLink="false">http://www.epanorama.net/newepa/?p=54897#comment-1546691</guid>
		<description><![CDATA[Open Source vs Proprietary: What organisations need to know
Meeting IT and business priorities with a hybrid approach to open source and proprietary solutions
https://www.sas.com/en_gb/whitepapers/open-source-vs-proprietary.html

Open source technologies, like Hadoop, R and Python, have been vital to the spread of big data. However, production deployment of these technologies has its own, often unexpected costs and projects are not necessarily succeeding as hoped. However, organisations see clear benefits from both open source and proprietary solutions, with a mixture of the two perceived as delivering the best return on investment.

This report, based on a survey of 300 senior IT and business decision-makers across the UK &amp; Ireland, aims to create a better understanding of the key considerations for open source and proprietary analytics technology, drivers for business transformation and any limitations to success.]]></description>
		<content:encoded><![CDATA[<p>Open Source vs Proprietary: What organisations need to know<br />
Meeting IT and business priorities with a hybrid approach to open source and proprietary solutions<br />
<a href="https://www.sas.com/en_gb/whitepapers/open-source-vs-proprietary.html" rel="nofollow">https://www.sas.com/en_gb/whitepapers/open-source-vs-proprietary.html</a></p>
<p>Open source technologies, like Hadoop, R and Python, have been vital to the spread of big data. However, production deployment of these technologies has its own, often unexpected costs and projects are not necessarily succeeding as hoped. However, organisations see clear benefits from both open source and proprietary solutions, with a mixture of the two perceived as delivering the best return on investment.</p>
<p>This report, based on a survey of 300 senior IT and business decision-makers across the UK &amp; Ireland, aims to create a better understanding of the key considerations for open source and proprietary analytics technology, drivers for business transformation and any limitations to success.</p>
]]></content:encoded>
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		<title>By: Tomi Engdahl</title>
		<link>https://www.epanorama.net/blog/2017/05/07/7-myths-about-open-sourcing-your-companys-software-opensource-com/comment-page-1/#comment-1546229</link>
		<dc:creator><![CDATA[Tomi Engdahl]]></dc:creator>
		<pubDate>Tue, 09 May 2017 12:47:53 +0000</pubDate>
		<guid isPermaLink="false">http://www.epanorama.net/newepa/?p=54897#comment-1546229</guid>
		<description><![CDATA[Myth #1: Open source is giving my business away for nothing
Myth #2: We&#039;ll lose control of everything
Myth #3: There&#039;s no value to open source
Myth #4: Someone will steal my idea
Myth #5: My bottom line will plummet
Myth #6: We&#039;ll go out of business
Myth #7: Competitors will steal our stuff

Making the choice to open source something can be scary, but it doesn&#039;t need to be. Open source is here to stay]]></description>
		<content:encoded><![CDATA[<p>Myth #1: Open source is giving my business away for nothing<br />
Myth #2: We&#8217;ll lose control of everything<br />
Myth #3: There&#8217;s no value to open source<br />
Myth #4: Someone will steal my idea<br />
Myth #5: My bottom line will plummet<br />
Myth #6: We&#8217;ll go out of business<br />
Myth #7: Competitors will steal our stuff</p>
<p>Making the choice to open source something can be scary, but it doesn&#8217;t need to be. Open source is here to stay</p>
]]></content:encoded>
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