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	<title>bearparc - Softwareentwicklung und Projektmanagement &#187; DataWarehouse</title>
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	<description>A software development blog for the qualified developer</description>
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		<title>Erfahrungsbericht : Konvertieren der Informatica Powerdesigner mappings zum Oracle DWH Builder</title>
		<link>http://www.bearparc.info/2007/05/22/konvertieren-der-informatica-powerdesigner-mappings-zum-oracle-dwh-builder/</link>
		<comments>http://www.bearparc.info/2007/05/22/konvertieren-der-informatica-powerdesigner-mappings-zum-oracle-dwh-builder/#comments</comments>
		<pubDate>Tue, 22 May 2007 12:14:16 +0000</pubDate>
		<dc:creator>Martin</dc:creator>
				<category><![CDATA[DataWarehouse]]></category>
		<category><![CDATA[ETL]]></category>

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		<description><![CDATA[Das automatisierte Konvertieren der Informatica mappings nach OWB ist hehre Ziel des OWB Toolkits. Die Informatica Metadaten werden in xml Format als Input verwendet, dadurch ist ein inkrementelles Konvertieren möglich. Das Toolkit automatisiert die Konvertierung nicht vollsständig, und diese ist nur in einem Flat-file möglich, die Fehler werden in einem logfile gespeichert, häufig auftretende Fehler [...]]]></description>
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		<title>Die häufigsten DWH Projektmanagementfehler</title>
		<link>http://www.bearparc.info/2007/04/30/die-haufigsten-dwh-projektmanagementfehler/</link>
		<comments>http://www.bearparc.info/2007/04/30/die-haufigsten-dwh-projektmanagementfehler/#comments</comments>
		<pubDate>Mon, 30 Apr 2007 09:49:48 +0000</pubDate>
		<dc:creator>Martin</dc:creator>
				<category><![CDATA[DataMart]]></category>
		<category><![CDATA[DataWarehouse]]></category>
		<category><![CDATA[ETL]]></category>
		<category><![CDATA[OLAP]]></category>
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		<category><![CDATA[Projektmanagement]]></category>

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		<description><![CDATA[1. Failing to Use a Methodology 2. Ineffective Project Team Structure 3. Failing to Involve the Business People 4. Failing to Have Application Releases 5. Failing to Have an Active Project Charter 6. Lack of a Readiness Assessment 7. Inadequate Testing 8. Underestimating Data Cleansing Efforts 9. Ignoring Metadata 10. Being a Slave to Project [...]]]></description>
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		<title>The different system challenge of OLTP and OLAP systems</title>
		<link>http://www.bearparc.info/2007/04/29/the-different-system-challenge-of-oltp-and-olap-systems/</link>
		<comments>http://www.bearparc.info/2007/04/29/the-different-system-challenge-of-oltp-and-olap-systems/#comments</comments>
		<pubDate>Sun, 29 Apr 2007 12:35:07 +0000</pubDate>
		<dc:creator>Martin</dc:creator>
				<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[DataMart]]></category>
		<category><![CDATA[DataWarehouse]]></category>
		<category><![CDATA[OLAP]]></category>
		<category><![CDATA[Oracle]]></category>

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		<description><![CDATA[The different system challenge of OLTP and OLAP systems OLTP OLAP fast insert and update fast joins and select, no inserts, no updates minimize redundant storage immediate access to current information access to aggregation of historical information maximize referential integrity oriented toward operation oriented toward decision support Analytical systems show the drill path or join [...]]]></description>
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		<title>MOLAP &#8211; Aggregieren eingebaute Logik</title>
		<link>http://www.bearparc.info/2007/04/04/molap-aggregieren-eingebaute-logik/</link>
		<comments>http://www.bearparc.info/2007/04/04/molap-aggregieren-eingebaute-logik/#comments</comments>
		<pubDate>Wed, 04 Apr 2007 14:19:50 +0000</pubDate>
		<dc:creator>Martin</dc:creator>
				<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[DataMart]]></category>
		<category><![CDATA[DataWarehouse]]></category>
		<category><![CDATA[OLAP]]></category>
		<category><![CDATA[Oracle]]></category>

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		<description><![CDATA[Automatic                              The method that Oracle OLAP determines is the best fit for the data. (Default) Linreg                                     Linear Regression. A method in which a linear relationship (y=a*x+b) is fitted to the data NLREG1 &#8211; 5                          Nonlinear Regression Method 1 &#8211; 5. DESMOOTH                         Double Exponential Smoothing. SESMOOTH                         Single Exponential Smoothing. SUM                                      Adds data values. (Default) SSUM                                    Scaled Sum [...]]]></description>
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		<title>ROLAP vs. MOLAP</title>
		<link>http://www.bearparc.info/2007/04/02/rolap-vs-molap/</link>
		<comments>http://www.bearparc.info/2007/04/02/rolap-vs-molap/#comments</comments>
		<pubDate>Mon, 02 Apr 2007 20:03:54 +0000</pubDate>
		<dc:creator>Martin</dc:creator>
				<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[DataMart]]></category>
		<category><![CDATA[DataWarehouse]]></category>
		<category><![CDATA[OLAP]]></category>
		<category><![CDATA[Oracle]]></category>

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		<description><![CDATA[ROLAP •Datenspeicherung in Tabellen •Metadaten: Dimensionen, Cubes,Maße •Berechnungen: SQL Erweiterungen •Optimierte Joins und Zugriffspfade •Typisch: Star-Schema •Indizierung, Materialized Views etc. um Datenbank zu beschleunigen MOLAP: •Datenspeicherung in speziellen Strukturen •Dimensionen, Cubes, Maße nativ •Berechnungen: komplette analytische Sprache inkl. umfangreicher Funktionen •Indizierung automatisch, Aggregation vordefiniert]]></description>
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		<title>MOLAP &#8211; eingebaute Funktionen</title>
		<link>http://www.bearparc.info/2007/03/23/molap-eingebaute-funktionen/</link>
		<comments>http://www.bearparc.info/2007/03/23/molap-eingebaute-funktionen/#comments</comments>
		<pubDate>Fri, 23 Mar 2007 18:26:12 +0000</pubDate>
		<dc:creator>Martin</dc:creator>
				<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[DataMart]]></category>
		<category><![CDATA[DataWarehouse]]></category>
		<category><![CDATA[OLAP]]></category>
		<category><![CDATA[Oracle]]></category>

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		<description><![CDATA[DEPRDECL, DEPRDECLSW, DEPRSL, DEPRSOYD                            Berechnet Abschreibungen auf verschiedene Weisen NPV                                                                                                              The NPV function computes the net present value of a series of cash flow values. IRR                                                                                                               The IRR function computes the internal rate of return associated with a series of                                                                                                                        cash flow values. Each value of the result is calculated to be the per-period [...]]]></description>
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