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	<title>Comments on: My actual column on data mining</title>
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		<title>By: The Monash Report&#187;Blog Archive &#187; The problem with dashboards, and business intelligence segmented</title>
		<link>http://www.monashreport.com/2006/09/11/my-actual-column-on-data-mining/#comment-44508</link>
		<dc:creator>The Monash Report&#187;Blog Archive &#187; The problem with dashboards, and business intelligence segmented</dc:creator>
		<pubDate>Thu, 29 Nov 2007 16:41:55 +0000</pubDate>
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		<description>[...] Deep analysis and decision support. Routine, scheduling reporting was covered in my first two categories. But this third one is where the bulk of ad hoc query and data mining fall. Generally, it’s where lots of specialized and/or calculation-intensive analytic technology comes into play. It’s also where the drilldown aspect of standard reporting shows up. Also, this is the area that is driving much of the recent transformation and disruption in the data warehouse market, because different kinds of BI need different kinds of data warehousing technology. [...]</description>
		<content:encoded><![CDATA[<p>[...] Deep analysis and decision support. Routine, scheduling reporting was covered in my first two categories. But this third one is where the bulk of ad hoc query and data mining fall. Generally, it’s where lots of specialized and/or calculation-intensive analytic technology comes into play. It’s also where the drilldown aspect of standard reporting shows up. Also, this is the area that is driving much of the recent transformation and disruption in the data warehouse market, because different kinds of BI need different kinds of data warehousing technology. [...]</p>
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		<title>By: DBMS2 &#8212; DataBase Management System Services&#187;Blog Archive &#187; Data mining is driving much of data warehousing</title>
		<link>http://www.monashreport.com/2006/09/11/my-actual-column-on-data-mining/#comment-2445</link>
		<dc:creator>DBMS2 &#8212; DataBase Management System Services&#187;Blog Archive &#187; Data mining is driving much of data warehousing</dc:creator>
		<pubDate>Wed, 04 Oct 2006 10:15:49 +0000</pubDate>
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		<description>[...] Until I did all this recent research on data warehousing, I didn’t realize just how big a role data mining plays in driving the whole thing. Basically, there are three things you can do with a data warehouse – classical BI, “operational” BI, and data mining. If we’re talking about long-running queries, that’s not operational BI, and it’s not all of classical BI either. The rest is data mining. Indeed, if you think back to what you know of the customer bases at data warehouse appliance vendors Netezza and DATallegro, there are a lot of credit-reporting-data types of users – i.e., data miners. And it’s hard to talk about uses for those appliances very long without SAS extracts and the like coming up. [...]</description>
		<content:encoded><![CDATA[<p>[...] Until I did all this recent research on data warehousing, I didn’t realize just how big a role data mining plays in driving the whole thing. Basically, there are three things you can do with a data warehouse – classical BI, “operational” BI, and data mining. If we’re talking about long-running queries, that’s not operational BI, and it’s not all of classical BI either. The rest is data mining. Indeed, if you think back to what you know of the customer bases at data warehouse appliance vendors Netezza and DATallegro, there are a lot of credit-reporting-data types of users – i.e., data miners. And it’s hard to talk about uses for those appliances very long without SAS extracts and the like coming up. [...]</p>
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		<title>By: The Monash Report&#187;Blog Archive &#187; KXEN and Verix try to disrupt the data mining market</title>
		<link>http://www.monashreport.com/2006/09/11/my-actual-column-on-data-mining/#comment-2444</link>
		<dc:creator>The Monash Report&#187;Blog Archive &#187; KXEN and Verix try to disrupt the data mining market</dc:creator>
		<pubDate>Wed, 04 Oct 2006 10:09:06 +0000</pubDate>
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		<description>[...] Data mining is hugely important, but it does have issues with accessibility. The traditional model of data mining goes something like this: [...]</description>
		<content:encoded><![CDATA[<p>[...] Data mining is hugely important, but it does have issues with accessibility. The traditional model of data mining goes something like this: [...]</p>
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		<title>By: The Monash Report&#187;Blog Archive &#187; Data mining requires data</title>
		<link>http://www.monashreport.com/2006/09/11/my-actual-column-on-data-mining/#comment-2438</link>
		<dc:creator>The Monash Report&#187;Blog Archive &#187; Data mining requires data</dc:creator>
		<pubDate>Wed, 04 Oct 2006 08:37:03 +0000</pubDate>
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		<description>[...] Data mining requires and justifies huge investments. The smallest part is the data mining software itself. A much bigger part is the investment in data warehouse technology, a subject about which I&#8217;ve been posting extensively recently on DBMS2.com. But there&#8217;s yet another part to the picture, namely investing in actually gathering data for analysis, that I&#8217;ve written about, most recently in a blog I posted elsewhere and am now copying below.  Analytic business processes &#8212; or the areas of overlap between analytics and business process &#8212; are poorly understood. Business Activity Monitoring and Operational BI? Great buzzwords, but [...]</description>
		<content:encoded><![CDATA[<p>[...] Data mining requires and justifies huge investments. The smallest part is the data mining software itself. A much bigger part is the investment in data warehouse technology, a subject about which I&#8217;ve been posting extensively recently on DBMS2.com. But there&#8217;s yet another part to the picture, namely investing in actually gathering data for analysis, that I&#8217;ve written about, most recently in a blog I posted elsewhere and am now copying below.  Analytic business processes &#8212; or the areas of overlap between analytics and business process &#8212; are poorly understood. Business Activity Monitoring and Operational BI? Great buzzwords, but [...]</p>
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