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	<title>CloverETL&#039;s Blog on Data Integration &#187; ETL</title>
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	<link>http://blog.cloveretl.com</link>
	<description>CloverETL tips and advice from data integration experts</description>
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		<title>Loading Data Warehouse &#8211; Fact Table Load Wizard</title>
		<link>http://blog.cloveretl.com/loading-data-warehouse-with-fact-table-load-wizard?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=loading-data-warehouse-with-fact-table-load-wizard</link>
		<comments>http://blog.cloveretl.com/loading-data-warehouse-with-fact-table-load-wizard#comments</comments>
		<pubDate>Tue, 24 Aug 2010 15:46:20 +0000</pubDate>
		<dc:creator>Viliam Wallace</dc:creator>
				<category><![CDATA[Using CloverETL]]></category>
		<category><![CDATA[data warehousing]]></category>
		<category><![CDATA[ETL]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=792</guid>
		<description><![CDATA[Users who are using CloverETL for data-warehousing often need to create a data transformation which populates DWH fact table with transaction data from source system. Each such transformation contains many components that join keys from dimensional tables to processing records. &#8230; <a href="http://blog.cloveretl.com/loading-data-warehouse-with-fact-table-load-wizard">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/loading-data-warehouse-with-fact-table-load-wizard/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
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		<item>
		<title>Building Data Warehouse with CloverETL: Slowly Changing Dimension Type 2</title>
		<link>http://blog.cloveretl.com/building-data-warehouse-scd2?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=building-data-warehouse-scd2</link>
		<comments>http://blog.cloveretl.com/building-data-warehouse-scd2#comments</comments>
		<pubDate>Thu, 27 May 2010 01:39:40 +0000</pubDate>
		<dc:creator>Petr Uher</dc:creator>
				<category><![CDATA[Using CloverETL]]></category>
		<category><![CDATA[CloverETL]]></category>
		<category><![CDATA[data warehousing]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[scd2]]></category>
		<category><![CDATA[slowly changing dimension]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=668</guid>
		<description><![CDATA[In the last part of our data warehouse (DWH) tutorial, I showed you how to load a dimension table that stores historical data according to the Slowly Changing Dimension Type 1 (SCD1). In today’s post, I will focus on a &#8230; <a href="http://blog.cloveretl.com/building-data-warehouse-scd2">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/building-data-warehouse-scd2/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>CloverETL as a High-throughput XML Processor</title>
		<link>http://blog.cloveretl.com/cloveretl-as-a-high-throughput-xml-processor?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=cloveretl-as-a-high-throughput-xml-processor</link>
		<comments>http://blog.cloveretl.com/cloveretl-as-a-high-throughput-xml-processor#comments</comments>
		<pubDate>Thu, 20 May 2010 15:19:34 +0000</pubDate>
		<dc:creator>Jakub Lehotsky</dc:creator>
				<category><![CDATA[Using CloverETL]]></category>
		<category><![CDATA[data parsing]]></category>
		<category><![CDATA[data processing]]></category>
		<category><![CDATA[DOM]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[SAX]]></category>
		<category><![CDATA[XML]]></category>
		<category><![CDATA[XMLSchema]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=654</guid>
		<description><![CDATA[XML is a markup language that has been around for some years now. Originally, it comes from the world of documents &#8211; used in web hypertext, word processors and other representations. Today, it is very popular in many areas, including &#8230; <a href="http://blog.cloveretl.com/cloveretl-as-a-high-throughput-xml-processor">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/cloveretl-as-a-high-throughput-xml-processor/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Data Profiling with CloverETL</title>
		<link>http://blog.cloveretl.com/data-profiling?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=data-profiling</link>
		<comments>http://blog.cloveretl.com/data-profiling#comments</comments>
		<pubDate>Wed, 31 Mar 2010 12:15:15 +0000</pubDate>
		<dc:creator>Agata Vackova</dc:creator>
				<category><![CDATA[Using CloverETL]]></category>
		<category><![CDATA[data profiling]]></category>
		<category><![CDATA[data quality]]></category>
		<category><![CDATA[data transformation]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[statistics]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=537</guid>
		<description><![CDATA[Before you start to develop any data transformation you should explore your data (make data profiling). There are a lot of tools on the market that can help you. But why to install and learn another software when you can &#8230; <a href="http://blog.cloveretl.com/data-profiling">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/data-profiling/feed</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>CloverETL 2.9 Released: Infobright Data Writer, Web Services Component and Other New Features.</title>
		<link>http://blog.cloveretl.com/cloveretl-version-2-9-was-released-it-adds-infobright-data-writer-web-services-component-and-other-new-features?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=cloveretl-version-2-9-was-released-it-adds-infobright-data-writer-web-services-component-and-other-new-features</link>
		<comments>http://blog.cloveretl.com/cloveretl-version-2-9-was-released-it-adds-infobright-data-writer-web-services-component-and-other-new-features#comments</comments>
		<pubDate>Mon, 01 Feb 2010 10:18:59 +0000</pubDate>
		<dc:creator>Lucie Felixova</dc:creator>
				<category><![CDATA[Developing Clover]]></category>
		<category><![CDATA[Aspell]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[Infobright]]></category>
		<category><![CDATA[LDAP]]></category>
		<category><![CDATA[release]]></category>
		<category><![CDATA[webservice]]></category>
		<category><![CDATA[XLS]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=412</guid>
		<description><![CDATA[New CloverETL version 2.9. was just released. This version brings a new Infobright Data Writer component, enhances the connectivity by adding Web Services component and adds features that simplify common data transformation tasks. New Features and Components: Infobright Data Writer In &#8230; <a href="http://blog.cloveretl.com/cloveretl-version-2-9-was-released-it-adds-infobright-data-writer-web-services-component-and-other-new-features">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/cloveretl-version-2-9-was-released-it-adds-infobright-data-writer-web-services-component-and-other-new-features/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Parallel Data Processing Comparison – CloverETL vs. Talend vs. Pentaho (Part 3)</title>
		<link>http://blog.cloveretl.com/parallel-data-processing-comparison-cloveretl-talend-pentaho-3?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=parallel-data-processing-comparison-cloveretl-talend-pentaho-3</link>
		<comments>http://blog.cloveretl.com/parallel-data-processing-comparison-cloveretl-talend-pentaho-3#comments</comments>
		<pubDate>Wed, 09 Dec 2009 15:09:09 +0000</pubDate>
		<dc:creator>Petr Uher</dc:creator>
				<category><![CDATA[Using CloverETL]]></category>
		<category><![CDATA[CloverETL]]></category>
		<category><![CDATA[CSV]]></category>
		<category><![CDATA[delimited data]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[ETL comparison]]></category>
		<category><![CDATA[ETL tool]]></category>
		<category><![CDATA[parallel processing]]></category>
		<category><![CDATA[pentaho]]></category>
		<category><![CDATA[performance]]></category>
		<category><![CDATA[talend]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=319</guid>
		<description><![CDATA[Performance comparison of reading/parsing CSV data and performing transformation operations like joining, filtering, aggregating. Compared are CloverETL, Pentaho, Talend. <a href="http://blog.cloveretl.com/parallel-data-processing-comparison-cloveretl-talend-pentaho-3">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/parallel-data-processing-comparison-cloveretl-talend-pentaho-3/feed</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>Parallel Data Processing Comparison – CloverETL vs. Talend vs. Pentaho (Part 2)</title>
		<link>http://blog.cloveretl.com/parallel-data-processing-comparison-cloveretl-talend-pentaho-2?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=parallel-data-processing-comparison-cloveretl-talend-pentaho-2</link>
		<comments>http://blog.cloveretl.com/parallel-data-processing-comparison-cloveretl-talend-pentaho-2#comments</comments>
		<pubDate>Wed, 11 Nov 2009 16:08:24 +0000</pubDate>
		<dc:creator>Petr Uher</dc:creator>
				<category><![CDATA[Using CloverETL]]></category>
		<category><![CDATA[CloverETL]]></category>
		<category><![CDATA[CSV]]></category>
		<category><![CDATA[delimited data]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[ETL comparison]]></category>
		<category><![CDATA[parallel processing]]></category>
		<category><![CDATA[pentaho]]></category>
		<category><![CDATA[performance]]></category>
		<category><![CDATA[talend]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=271</guid>
		<description><![CDATA[Before we will release a complete comparison of open source ETL tools and after a success of my previous blog post I decided to publish the second transformation that we used in the comparison. The second transformation is also based &#8230; <a href="http://blog.cloveretl.com/parallel-data-processing-comparison-cloveretl-talend-pentaho-2">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/parallel-data-processing-comparison-cloveretl-talend-pentaho-2/feed</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>ParallelReader Component: Performance Boost in Data Processing</title>
		<link>http://blog.cloveretl.com/parallel-reader?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=parallel-reader</link>
		<comments>http://blog.cloveretl.com/parallel-reader#comments</comments>
		<pubDate>Fri, 23 Oct 2009 11:36:51 +0000</pubDate>
		<dc:creator>Martin Zatopek</dc:creator>
				<category><![CDATA[Using CloverETL]]></category>
		<category><![CDATA[CloverETL]]></category>
		<category><![CDATA[CSV]]></category>
		<category><![CDATA[data parsing]]></category>
		<category><![CDATA[data processing]]></category>
		<category><![CDATA[delimited file]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[parallel processing]]></category>
		<category><![CDATA[ParallelReader]]></category>
		<category><![CDATA[performance]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=252</guid>
		<description><![CDATA[In October release 2.8.1 of Clover we introduced a new component which definitely should attract your attention – the Parallel Reader. The name itself already suggests the goal of the component – improve reading speed by going parallel. The component &#8230; <a href="http://blog.cloveretl.com/parallel-reader">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/parallel-reader/feed</wfw:commentRss>
		<slash:comments>2</slash:comments>
		</item>
		<item>
		<title>Building Data Warehouse with CloverETL: Slowly Changing Dimension Type 1</title>
		<link>http://blog.cloveretl.com/building-data-warehouse-scd1?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=building-data-warehouse-scd1</link>
		<comments>http://blog.cloveretl.com/building-data-warehouse-scd1#comments</comments>
		<pubDate>Thu, 08 Oct 2009 10:21:56 +0000</pubDate>
		<dc:creator>Petr Uher</dc:creator>
				<category><![CDATA[Using CloverETL]]></category>
		<category><![CDATA[CloverETL]]></category>
		<category><![CDATA[data warehousing]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[SCD1]]></category>
		<category><![CDATA[slowly changing dimension]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=213</guid>
		<description><![CDATA[The very typical usage of ETL tools is loading the data warehouse (DWH). So I decided to write a tutorial that will describe typical data warehouse tasks (slowly changing dimensions, date dimension, filling fact tables) and propose solutions with using &#8230; <a href="http://blog.cloveretl.com/building-data-warehouse-scd1">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/building-data-warehouse-scd1/feed</wfw:commentRss>
		<slash:comments>1</slash:comments>
		</item>
		<item>
		<title>Processing Data from QuickBase</title>
		<link>http://blog.cloveretl.com/processing-data-from-quickbase?utm_source=rss&#038;utm_medium=rss&#038;utm_campaign=processing-data-from-quickbase</link>
		<comments>http://blog.cloveretl.com/processing-data-from-quickbase#comments</comments>
		<pubDate>Wed, 02 Sep 2009 08:34:40 +0000</pubDate>
		<dc:creator>Martin Zatopek</dc:creator>
				<category><![CDATA[Using CloverETL]]></category>
		<category><![CDATA[CloverETL]]></category>
		<category><![CDATA[connectivity]]></category>
		<category><![CDATA[connector]]></category>
		<category><![CDATA[data processing]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[Intuit]]></category>
		<category><![CDATA[QuickBase]]></category>

		<guid isPermaLink="false">http://blog.cloveretl.com/?p=161</guid>
		<description><![CDATA[We have great news for users of on-line database QuickBase from Intuit . CloverETL became a next tool which can be used to manipulate the data in this database. Now you can work with data in QuickBase without restraints and &#8230; <a href="http://blog.cloveretl.com/processing-data-from-quickbase">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
		<wfw:commentRss>http://blog.cloveretl.com/processing-data-from-quickbase/feed</wfw:commentRss>
		<slash:comments>0</slash:comments>
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