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商业智能简介

商业智能简介

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Bi Bi Presentation Transcript

  • / BIjeffjie@fallever.comhttp://twitter.com/jeff_kit
  • 1.2.3. jeff@fallever.com
  • jeff@fallever.com
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  • Peterjeff@fallever.com
  • Peterjeff@fallever.com
  • Peterjeff@fallever.com
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  • • / •jeff@fallever.com
  • Text ETL Textjeff@fallever.com
  • 1.2.3. jeff@fallever.com
  • • ETL • • OLAP-- • Cube-- MDX •jeff@fallever.com
  • ETL Transform Load XML Extractjeff@fallever.com
  • OLAP jeff@fallever.com
  • 1.OLAP jeff@fallever.com
  • 1.OLAP 2. jeff@fallever.com
  • 1.OLAP 2. 3. jeff@fallever.com
  • OL(X)P OLTP = ( ) OnLine Transaction Processing 1960S OLAP = ( ) OnLine Analytical Processing 1993 E.F.Coddjeff@fallever.com
  • OLTP T-SQL OAselect amount from sales where customer = 1 jeff@fallever.com
  • OLAP MDXCubeSELECT [Product] ON COLUMS,[Location] ON ROWS jeff@fallever.com
  • OLAP OLTPjeff@fallever.com
  • OLAP OLTPjeff@fallever.com
  • OLAP OLTPjeff@fallever.com
  • “ ” 5000 ID10909002 10.8 2010-10-20 50 jeff@fallever.com
  • 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000jeff@fallever.com
  • OLTP 1.select count( ), , from group by 2. 1000000 2000000 ......... ......... .......... 3.jeff@fallever.com
  • OLAP select [ ] on columns,[ ] on rows from [ ] 2 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 ....... ....... ........ ........ ........ ........jeff@fallever.com
  • OLTP 2 OLAPjeff@fallever.com
  • 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000jeff@fallever.com
  • OLTP 1. 2.select count( ), , ( ) from group by , ( ) 3. 8 1000000 2000000 ......... ......... .......... 4.jeff@fallever.com
  • OLAP select [ ] on columns,[ ].[ ].children on rows from [ ] 2 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 2,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 3,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 1,000,000,000 4,000,000,000 5,000,000,000jeff@fallever.com
  • OLTP OLAPjeff@fallever.com
  • OLAPjeff@fallever.com
  • -Cube T-Shit Clothes hatsjeff@fallever.com
  • -Cube (Dimension) T-Shit Clothes hatsjeff@fallever.com
  • -Cube (Dimension) (Measure) T-Shit Clothes hatsjeff@fallever.com
  • -Cube (Dimension) (Measure)Hierarchy T-Shit Clothes hats jeff@fallever.com
  • -MDXSELECT{[ ],[ ]} ON ,FROM [ ]WHERE ([ ]) 128 PS. COLUMNS(0) ROWS(1) PAGES(2) SECTIONS(3) CHAPTERS(4) jeff@fallever.com
  • | | | | |jeff@fallever.com
  • 1.2.3. jeff@fallever.com
  • • ETL • • OLAP • •jeff@fallever.com
  • BIjeff@fallever.com
  • BI BIRTjeff@fallever.com
  • Introduction to data cube http://www2.cs.uregina.ca/~dbd/cs831/notes/dcubes/dcubes.htmlRapid Miner http://rapid-i.com/content/view/181/90/SpagoBI http://www.spagoworld.org/xwiki/bin/view/SpagoBI/Jasperreports http://jasperforge.org/projects/jasperreportspentaho http://www.pentaho.com/pentaho http://community.pentaho.com/projects/bi_platform/Palo for Excel http://www.palo.net/en/ MicroSoft SQL Server 2005 http://book.douban.com/subject/3016243/ http://en.wikipedia.org/wiki/Business_intelligence_toolsjeff@fallever.com
  • jeff@fallever.com
  • Bio: &Twitter: @jeff_kit jeff@fallever.comjeff@fallever.com