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	<title>Gigaom Search &#187; predictive analytics</title>
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		<title>This company says it can fix the sales process using lots of data science, and even more data</title>
		<link>https://gigaom.com/2014/10/10/this-company-says-it-can-fix-the-sales-process-using-lots-of-data-science-and-even-more-data/</link>
		<comments>https://gigaom.com/2014/10/10/this-company-says-it-can-fix-the-sales-process-using-lots-of-data-science-and-even-more-data/#comments</comments>
		<pubDate>Fri, 10 Oct 2014 18:46:25 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[data science]]></category>
		<category><![CDATA[machine learning]]></category>
		<category><![CDATA[neural networks]]></category>
		<category><![CDATA[predictive analytics]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=880029</guid>
		<description><![CDATA[Provo, Utah–based sales automation company InsideSales has always been interested in applying data analysis to mountains of sales data. After delivering on this mission last year, the company is now ramping&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/10/10/this-company-says-it-can-fix-the-sales-process-using-lots-of-data-science-and-even-more-data/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		<title>Predictive analytics and data-blending specialist Alteryx raises $60M</title>
		<link>https://gigaom.com/2014/10/06/predictive-analytics-and-data-blending-specialist-alteryx-raises-60m/</link>
		<comments>https://gigaom.com/2014/10/06/predictive-analytics-and-data-blending-specialist-alteryx-raises-60m/#comments</comments>
		<pubDate>Mon, 06 Oct 2014 14:58:39 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Alteryx]]></category>
		<category><![CDATA[in memory processing]]></category>
		<category><![CDATA[predictive analytics]]></category>
		<category><![CDATA[predictive modeling]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=878551</guid>
		<description><![CDATA[Alteryx has raised $60 million to help expand its fast-growing business, which straddles the middle ground between Excel and SPSS by trying to turn data blending and predictive modeling into self-service experiences.]]></description>
		<wfw:commentRss>https://gigaom.com/2014/10/06/predictive-analytics-and-data-blending-specialist-alteryx-raises-60m/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Sector Roadmap: machine learning and predictive analytics</title>
		<link>http://research.gigaom.com/report/sector-roadmap-machine-learning-and-predictive-analytics/</link>
		<comments>http://research.gigaom.com/report/sector-roadmap-machine-learning-and-predictive-analytics/#comments</comments>
		<pubDate>Thu, 25 Sep 2014 12:06:56 +0000</pubDate>
		<dc:creator><![CDATA[Mark Tabladillo]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[data science]]></category>
		<category><![CDATA[predictive analytics]]></category>

		<guid isPermaLink="false">http://research.gigaom.com/?post_type=go-report&#038;p=237600/</guid>
		<description><![CDATA[A mixture of big data, improved algorithms, increasingly cheaper storage, and cloud-hosted options has fueled a surge in new data mining and machine learning products.]]></description>
		<wfw:commentRss>http://research.gigaom.com/report/sector-roadmap-machine-learning-and-predictive-analytics/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Google has open sourced a tool for inferring cause from correlations</title>
		<link>https://gigaom.com/2014/09/11/google-has-open-sourced-a-tool-for-inferring-cause-from-correlations/</link>
		<comments>https://gigaom.com/2014/09/11/google-has-open-sourced-a-tool-for-inferring-cause-from-correlations/#comments</comments>
		<pubDate>Thu, 11 Sep 2014 17:32:42 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Causality]]></category>
		<category><![CDATA[data science]]></category>
		<category><![CDATA[open source]]></category>
		<category><![CDATA[predictive analytics]]></category>
		<category><![CDATA[R]]></category>
		<category><![CDATA[statistical analysis]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NSDQ:GOOG]]></category>
		
		<guid isPermaLink="false">http://gigaom.com/?p=872423</guid>
		<description><![CDATA[Google open sourced a new package for the R statistical computing software that's designed to help users infer whether a particular action really did cause subsequent activity. Google has been using&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/09/11/google-has-open-sourced-a-tool-for-inferring-cause-from-correlations/feed/</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>How IT can blend massive connectivity with cognitive computing to enable insights</title>
		<link>http://research.gigaom.com/report/how-it-can-blend-massive-connectivity-with-cognitive-computing-to-enable-insights/</link>
		<comments>http://research.gigaom.com/report/how-it-can-blend-massive-connectivity-with-cognitive-computing-to-enable-insights/#comments</comments>
		<pubDate>Mon, 25 Aug 2014 21:26:23 +0000</pubDate>
		<dc:creator><![CDATA[David Loshin]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Ambient intelligence]]></category>
		<category><![CDATA[analytics algorithms]]></category>
		<category><![CDATA[predictive analytics]]></category>

		<guid isPermaLink="false">http://research.gigaom.com/?post_type=go-report&#038;p=235810/</guid>
		<description><![CDATA[Predictive analytics methods are extremely useful when dealing with the likes of fraudulent activity, imminent hardware failures, or credit risk. But these analytics algorithms are still somewhat limited. Here’s what IT&#8230;]]></description>
		<wfw:commentRss>http://research.gigaom.com/report/how-it-can-blend-massive-connectivity-with-cognitive-computing-to-enable-insights/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Machine Learning, in Redmond and beyond</title>
		<link>http://research.gigaom.com/2014/07/machine-learning-in-redmond-and-beyond/</link>
		<comments>http://research.gigaom.com/2014/07/machine-learning-in-redmond-and-beyond/#comments</comments>
		<pubDate>Wed, 09 Jul 2014 13:00:34 +0000</pubDate>
		<dc:creator><![CDATA[Andrew Brust]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Analysis Services]]></category>
		<category><![CDATA[predictive analytics]]></category>
		<category><![CDATA[SQL Server]]></category>
<category domain="http://search.gigaom.com/stock/"><![CDATA[NASDAQ:MSFT]]></category>
		<category domain="http://search.gigaom.com/stock/"><![CDATA[NSDQ:MSFT]]></category>
		
		<guid isPermaLink="false">http://research.gigaom.com/?p=232738</guid>
		<description><![CDATA[Microsoft's been in the machine learning game for almost 15 years, announcing a revamped offering last month. What does Redmond's Machine Learning history tell us about the market's future?]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>New analytics capabilities go mainstream</title>
		<link>http://research.gigaom.com/2014/06/new-analytics-capabilities-go-mainstream/</link>
		<comments>http://research.gigaom.com/2014/06/new-analytics-capabilities-go-mainstream/#comments</comments>
		<pubDate>Wed, 18 Jun 2014 13:55:48 +0000</pubDate>
		<dc:creator><![CDATA[Laura Stuart]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[in-memory dataa]]></category>
		<category><![CDATA[predictive analytics]]></category>
		<category><![CDATA[streaming analytics]]></category>

		<guid isPermaLink="false">http://research.gigaom.com/?p=231522</guid>
		<description><![CDATA[In his Weekly Update, Andrew Brust, the Gigaom Research research director for data, looks at the dynamics as new predictive, streaming and in-memory analytics gain momentum in the market. He notes that&#8230;]]></description>
		<wfw:commentRss>http://research.gigaom.com/2014/06/new-analytics-capabilities-go-mainstream/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Advanced Analytics for All</title>
		<link>http://research.gigaom.com/webinar/advanced-analytics-for-all/</link>
		<comments>http://research.gigaom.com/webinar/advanced-analytics-for-all/#comments</comments>
		<pubDate>Wed, 21 May 2014 20:00:00 +0000</pubDate>
		<dc:creator><![CDATA[Andrew Brust]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[predictive analytics]]></category>

		<guid isPermaLink="false">http://research.gigaom.com/?post_type=go_webinar&#038;p=229226</guid>
		<description><![CDATA[Technology lays the groundwork for change, but making that technology approachable creates a revolution. The GUI – not the PC – brought computing to the masses, and the browser – not&#8230;]]></description>
		<wfw:commentRss>http://research.gigaom.com/webinar/advanced-analytics-for-all/feed/</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Machine learning startup Context Relevant raises $21M in series B funding</title>
		<link>https://gigaom.com/2014/05/20/machine-learning-startup-context-relevant-raises-21m-in-series-b-funding/</link>
		<comments>https://gigaom.com/2014/05/20/machine-learning-startup-context-relevant-raises-21m-in-series-b-funding/#comments</comments>
		<pubDate>Tue, 20 May 2014 15:44:34 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[Context Relevant]]></category>
		<category><![CDATA[predictive analytics]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=843119</guid>
		<description><![CDATA[Context Relevant, a Seattle-based startup that promises to create accurate predictive models in a hurry, even across large datasets, has raised a $21 million series B round of venture capital. Formation 8&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/05/20/machine-learning-startup-context-relevant-raises-21m-in-series-b-funding/feed/</wfw:commentRss>
		<slash:comments>3</slash:comments>
		</item>
		<item>
		<title>Predictive marketing startup 6Sense launches with $12M in funding</title>
		<link>https://gigaom.com/2014/05/19/predictive-marketing-startup-6sense-launches-with-12m-in-funding/</link>
		<comments>https://gigaom.com/2014/05/19/predictive-marketing-startup-6sense-launches-with-12m-in-funding/#comments</comments>
		<pubDate>Mon, 19 May 2014 14:15:56 +0000</pubDate>
		<dc:creator><![CDATA[Derrick Harris]]></dc:creator>
				<category><![CDATA[Uncategorized]]></category>
		<category><![CDATA[marketing data]]></category>
		<category><![CDATA[predictive analytics]]></category>

		<guid isPermaLink="false">http://gigaom.com/?p=842755</guid>
		<description><![CDATA[6Sense, a startup using machine learning to help companies predict who'll buy their products, launched on Monday along with $12 million in venture capital from Battery Ventures and Venrock. The company claims&#8230;]]></description>
		<wfw:commentRss>https://gigaom.com/2014/05/19/predictive-marketing-startup-6sense-launches-with-12m-in-funding/feed/</wfw:commentRss>
		<slash:comments>1</slash:comments>
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