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				<title>A Big Data Course</title>
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				<pubDate>Wed, 12 Mar 2014 09:26:36 +0000</pubDate>
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				<description>&lt;p&gt;The published diagram is to detail a setup of a Big Data Course.&lt;/p&gt;&#xA;&lt;ol&gt;&#xA;&lt;li&gt;Fundamentals on databases (SQL and NoSQL), statistics (the R framework) and graph databases&lt;/li&gt;&#xA;&lt;li&gt;The focus is on the Hadoop eco-system and its programming paradigm, MapReduce&lt;/li&gt;&#xA;&lt;li&gt;MapReduce is available to be used with easier to master high level query languages like Pig and Hive&lt;/li&gt;&#xA;&lt;li&gt;While Hadoop is for batch processing there are other usage areas:&#xA;&lt;ul&gt;&#xA;&lt;li&gt;Real-time data access by HBase NoSQL daemon&lt;/li&gt;&#xA;&lt;li&gt;Fast but lower data volume processor, Spark&lt;/li&gt;&#xA;&lt;li&gt;Machine learning framework that can be run on top of Hadoop: Mahout&lt;/li&gt;&#xA;&lt;/ul&gt;&#xA;&lt;/li&gt;&#xA;&lt;li&gt;To be able to use these tools a well built, secure cluster is to be planned and developed, then operated securely&lt;/li&gt;&#xA;&lt;li&gt;After the data analysis is done, final steps of visualization are detailed - to make an impact by using the achieved analytic results&lt;/li&gt;&#xA;&lt;/ol&gt;&#xA;&lt;p&gt;A &lt;a href=&#34;http://www.u-szeged.hu/tanrend?browse=kurzus&amp;amp;kurzusId=1591460&amp;amp;ciklusId=2014-2015-1#browse&#34;&gt;derivative of the course&lt;/a&gt; is held at the University of Szeged. &lt;a href=&#34;https://dataprd.com/images/uploads/2014/08/Course.png&#34;&gt;&lt;img src=&#34;https://dataprd.com/images/uploads/2014/08/Course.png&#34; alt=&#34;Big Data Course&#34;&gt;&lt;/a&gt;&lt;/p&gt;</description>
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