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	<title>bearparc - Softwareentwicklung und Projektmanagement &#187; DataMart</title>
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	<link>http://www.bearparc.info</link>
	<description>A software development blog for the qualified developer</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>
		<category><![CDATA[Oracle]]></category>
		<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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		</item>
		<item>
		<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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		<slash:comments>0</slash:comments>
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		<item>
		<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>

		<guid isPermaLink="false">http://www.bearparc.info/2007/04/04/molap-aggregieren-eingebaute-logik/</guid>
		<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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		<slash:comments>0</slash:comments>
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		<item>
		<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>

		<guid isPermaLink="false">http://www.bearparc.info/2007/04/02/rolap-vs-molap/</guid>
		<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>

		<guid isPermaLink="false">http://www.bearparc.info/2007/03/23/molap-eingebaute-funktionen/</guid>
		<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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		<slash:comments>0</slash:comments>
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		<item>
		<title>Oracle BI &#8211; Erzeugen eines analytic workspace im Oracle Analytic Workspace manager</title>
		<link>http://www.bearparc.info/2007/03/22/oracle-bi-erzeugen-eines-analytic-workspace-im-oracle-analytic-workspace-manager/</link>
		<comments>http://www.bearparc.info/2007/03/22/oracle-bi-erzeugen-eines-analytic-workspace-im-oracle-analytic-workspace-manager/#comments</comments>
		<pubDate>Thu, 22 Mar 2007 10:00:50 +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>

		<guid isPermaLink="false">http://www.bearparc.info/2007/03/22/oracle-bi-erzeugen-eines-analytic-workspace-im-oracle-analytic-workspace-manager/</guid>
		<description><![CDATA[Voraussetzungen: Oracle10g Enterprise Edition mit RDBMS 10.1.0.4.0 patch. Analytic Workspace Manager 10.1.0.4 1. tablespace und data files erzeugen cd wkdir (workingdirectory) sqlplus /nolog connect / as sysdba CREATE TABLESPACE GLOBAL (oder AWM etc...) DATAFILE 'd:/oracle/product10.1.0/oradata/orcl/GLOBAL.DBF' SIZE 90M AUTOEXTEND ON NEXT 5M; CREATE TEMPORARY TABLESPACE GLOBAL_TEMP TEMPFILE 'd:/oracle/product10.1.0/oradata/orcl/GLOBAL_TEMP.DBF' SIZE 90M AUTOEXTEND ON NEXT 5M UNIFORM SIZE [...]]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>OLAP &#8211; Design des logischen Datenmodells</title>
		<link>http://www.bearparc.info/2007/03/21/olap-design-eines-logischen-datenmodells/</link>
		<comments>http://www.bearparc.info/2007/03/21/olap-design-eines-logischen-datenmodells/#comments</comments>
		<pubDate>Wed, 21 Mar 2007 16:05:24 +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>

		<guid isPermaLink="false">http://www.bearparc.info/2007/03/21/olap-design-eines-logischen-datenmodells/</guid>
		<description><![CDATA[Dimensions  beschreiben die mögliche Sicht auf eine Kennzahl.  dienen der orthogonalen Strukturierung des Datenraums  endliche Menge von n Hierachieobjekten, die iene semantische Beziehung aufweisen Beispiel: Produkt, Wertpapier, Zeit, Geographie  Level Unterkategorien der Dimension Beispiel : Dimension Geodaten, Level Nation, Level Region. Hierachien Hierachien organisieren die Levels für jede Dimension. Um eine Hierachie zu identifizieren werden [...]]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>Materialized View &#8211; Codebeispiel Join</title>
		<link>http://www.bearparc.info/2007/03/17/materilized-view-codebeispiel-join/</link>
		<comments>http://www.bearparc.info/2007/03/17/materilized-view-codebeispiel-join/#comments</comments>
		<pubDate>Sat, 17 Mar 2007 14:26:11 +0000</pubDate>
		<dc:creator>Martin</dc:creator>
				<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[DataMart]]></category>
		<category><![CDATA[DataWarehouse]]></category>
		<category><![CDATA[Oracle]]></category>

		<guid isPermaLink="false">http://www.bearparc.info/2007/03/17/materilized-view-codebeispiel-join/</guid>
		<description><![CDATA[Codebeispiel join: CREATE MATERIALIZED VIEW stock_sect ENABLE QUERY REWRITE AS SELECT s.*, sectname, Sect_ID FROM stock s, sect t WHERE s.ISIN = t.ISIN;]]></description>
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		<slash:comments>0</slash:comments>
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		<item>
		<title>materialized view &#8211; Codebeispiel Aggregation</title>
		<link>http://www.bearparc.info/2007/03/17/materialized-view-codebeispiel-aggregation/</link>
		<comments>http://www.bearparc.info/2007/03/17/materialized-view-codebeispiel-aggregation/#comments</comments>
		<pubDate>Sat, 17 Mar 2007 12:57:15 +0000</pubDate>
		<dc:creator>Martin</dc:creator>
				<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[DataMart]]></category>
		<category><![CDATA[DataWarehouse]]></category>
		<category><![CDATA[Oracle]]></category>
		<category><![CDATA[SQL]]></category>

		<guid isPermaLink="false">http://www.bearparc.info/2007/03/17/materialized-view-codebeispiel-aggregation/</guid>
		<description><![CDATA[Codebeispiel Aggregation: CREATE MATERIALIZED VIEW stocks_summary ENABLE QUERY REWRITE AS SELECT ISIN, Volume, Kurs FROM stocks GROUP BY ISIN, Kurs;]]></description>
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		<slash:comments>0</slash:comments>
		</item>
		<item>
		<title>materialized views- Privilegien</title>
		<link>http://www.bearparc.info/2007/03/17/materialized-views-privilegien/</link>
		<comments>http://www.bearparc.info/2007/03/17/materialized-views-privilegien/#comments</comments>
		<pubDate>Sat, 17 Mar 2007 12:32:19 +0000</pubDate>
		<dc:creator>Martin</dc:creator>
				<category><![CDATA[Business Intelligence]]></category>
		<category><![CDATA[DataMart]]></category>
		<category><![CDATA[Oracle]]></category>
		<category><![CDATA[SQL]]></category>

		<guid isPermaLink="false">http://www.bearparc.info/2007/03/17/materialized-views-privilegien/</guid>
		<description><![CDATA[Zur Erstellung ist sind folgende System Privilegien notwendig Create materialized view oder Create any materialized view Für das Query rewrite query rewrite oder global query rewrite query_rewrite_enabled muss in init.ora auf true stehen. bei automatischen Refresh (incremental, fast)muss mindestens ein Job-queue konfiguriert sein. Codebeispiel: Rechtevergabe: GRANT CREATE MATERIALIZED VIEW TO olap; GRANT QUERY REWRITE TO [...]]]></description>
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