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	<title>Comments on: Netflix shows off how it does Hadoop in the cloud</title>
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		<title>By: Laxmi Patel</title>
		<link>http://gigaom.com/2013/01/10/netflix-shows-off-its-hadoop-architecture/#comment-1304052</link>
		<dc:creator><![CDATA[Laxmi Patel]]></dc:creator>
		<pubDate>Sat, 26 Jan 2013 17:31:02 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=600969#comment-1304052</guid>
		<description><![CDATA[35+ Speakers, 20+ Sessions, 18+ Exhibitors are attending at Global Big Data Conference on Jan 28 2013, Santa Clara Convention Center. Register on http://globalbigdataconference.com/registration.php to attend the event. Get 20% offer using the Discount code BLOG.]]></description>
		<content:encoded><![CDATA[<p>35+ Speakers, 20+ Sessions, 18+ Exhibitors are attending at Global Big Data Conference on Jan 28 2013, Santa Clara Convention Center. Register on <a href="http://globalbigdataconference.com/registration.php" rel="nofollow">http://globalbigdataconference.com/registration.php</a> to attend the event. Get 20% offer using the Discount code BLOG.</p>
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		<title>By: Shalin Shah</title>
		<link>http://gigaom.com/2013/01/10/netflix-shows-off-its-hadoop-architecture/#comment-1300851</link>
		<dc:creator><![CDATA[Shalin Shah]]></dc:creator>
		<pubDate>Fri, 18 Jan 2013 18:32:14 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=600969#comment-1300851</guid>
		<description><![CDATA[As companies gather greater volumes of disparate kinds of data (i.e., Both structured and unstructured), they are also looking for solutions that can scale. This kind of data includes data generated by social media activity streams, existing ERP systems, and network data. Continuous, real-time analysis of large amounts of data is becoming more prevalent. For example, telecommunications service providers need real-time visibility into activation system service orders, showing activation times and lists of potential exceptions. Internet service providers need real-time visibility across field work operations to improve the management and prioritization of work orders, installer schedules, and maintenance requests. The recent buzz around “Big Data” solutions is growing louder, but only Operational Intelligence solutions are purpose-built for analyzing Big Data.]]></description>
		<content:encoded><![CDATA[<p>As companies gather greater volumes of disparate kinds of data (i.e., Both structured and unstructured), they are also looking for solutions that can scale. This kind of data includes data generated by social media activity streams, existing ERP systems, and network data. Continuous, real-time analysis of large amounts of data is becoming more prevalent. For example, telecommunications service providers need real-time visibility into activation system service orders, showing activation times and lists of potential exceptions. Internet service providers need real-time visibility across field work operations to improve the management and prioritization of work orders, installer schedules, and maintenance requests. The recent buzz around “Big Data” solutions is growing louder, but only Operational Intelligence solutions are purpose-built for analyzing Big Data.</p>
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		<title>By: Mark</title>
		<link>http://gigaom.com/2013/01/10/netflix-shows-off-its-hadoop-architecture/#comment-1297859</link>
		<dc:creator><![CDATA[Mark]]></dc:creator>
		<pubDate>Sat, 12 Jan 2013 05:16:09 +0000</pubDate>
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		<description><![CDATA[The good news is that Netflix is open sourcing lots of stuff that will help us small guys. :)]]></description>
		<content:encoded><![CDATA[<p>The good news is that Netflix is open sourcing lots of stuff that will help us small guys. :)</p>
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		<title>By: Bruno Aziza</title>
		<link>http://gigaom.com/2013/01/10/netflix-shows-off-its-hadoop-architecture/#comment-1297777</link>
		<dc:creator><![CDATA[Bruno Aziza]]></dc:creator>
		<pubDate>Fri, 11 Jan 2013 22:15:35 +0000</pubDate>
		<guid isPermaLink="false">http://gigaom.com/?p=600969#comment-1297777</guid>
		<description><![CDATA[Love these stories Derrick.  This one reminds me a lot of the one you&#039;ve written about Facebook earlier in the year.  The key question for each of these profiles of me is: how can companies of all sizes learn from such examples?  

Some kind of checklist would be interesting to share - there are millions of companies that need help with Big Data but the task still seems daunting to them because they assume that they need the big teams, big hardware and big budgets that these leaders have.

Analytically Yours,
Bruno Aziza
www.sisense.com]]></description>
		<content:encoded><![CDATA[<p>Love these stories Derrick.  This one reminds me a lot of the one you&#8217;ve written about Facebook earlier in the year.  The key question for each of these profiles of me is: how can companies of all sizes learn from such examples?  </p>
<p>Some kind of checklist would be interesting to share &#8211; there are millions of companies that need help with Big Data but the task still seems daunting to them because they assume that they need the big teams, big hardware and big budgets that these leaders have.</p>
<p>Analytically Yours,<br />
Bruno Aziza<br />
<a href="http://www.sisense.com" rel="nofollow">http://www.sisense.com</a></p>
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