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This document discusses concepts related to business intelligence (BI) including Extract, Transform, Load (ETL), Online Analytical Processing (OLAP), data cubes, and multidimensional expressions (MDX). It provides examples of how OLAP uses data cubes and MDX to enable fast analytical queries across large datasets for reporting and analysis, unlike traditional online transaction processing (OLTP). Common BI tools are also listed.
![OLAP
MDX
Cube
SELECT [Product] ON COLUMS,[Location] ON ROWS
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![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
....... ....... ........ ........ ........ ........
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![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 5,000,000,000
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![-MDX
SELECT
{[ ],[ ]} ON ,
FROM [ ]
WHERE ([ ])
128
PS. COLUMNS(0) ROWS(1)
PAGES(2) SECTIONS(3) CHAPTERS(4)
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Bi
- 1. / BI jeffjie@fallever.com http://twitter.com/jeff_kit
- 15. ? / ? jeff@fallever.com
- 16. Text ETL Text jeff@fallever.com
- 18. ? ETL ? ? OLAP-- ? Cube-- MDX ? jeff@fallever.com
- 19. ETL Transform Load XML Extract jeff@fallever.com
- 22. 1. OLAP 2. jeff@fallever.com
- 23. 1. OLAP 2. 3. jeff@fallever.com
- 24. OL(X)P OLTP = ( ) OnLine Transaction Processing 1960S OLAP = ( ) OnLine Analytical Processing 1993 E.F.Codd jeff@fallever.com
- 25. OLTP T-SQL OA select amount from sales where customer = 1 jeff@fallever.com
- 26. OLAP MDX Cube SELECT [Product] ON COLUMS,[Location] ON ROWS jeff@fallever.com
- 27. OLAP OLTP jeff@fallever.com
- 28. OLAP OLTP jeff@fallever.com
- 29. OLAP OLTP jeff@fallever.com
- 30. ¡° ¡± 5000 ID 10909002 10.8 2010-10-20 50 jeff@fallever.com
- 31. 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
- 32. OLTP 1.select count( ), , from group by 2. 1000000 2000000 ......... ......... .......... 3. jeff@fallever.com
- 33. 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
- 34. OLTP 2 OLAP jeff@fallever.com
- 35. 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
- 36. OLTP 1. 2.select count( ), , ( ) from group by , ( ) 3. 8 1000000 2000000 ......... ......... .......... 4. jeff@fallever.com
- 37. 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 5,000,000,000 jeff@fallever.com
- 38. OLTP OLAP jeff@fallever.com
- 40. -Cube T-Shit Clothes hats jeff@fallever.com
- 41. -Cube (Dimension) T-Shit Clothes hats jeff@fallever.com
- 42. -Cube (Dimension) (Measure) T-Shit Clothes hats jeff@fallever.com
- 43. -Cube (Dimension) (Measure) Hierarchy T-Shit Clothes hats jeff@fallever.com
- 44. -MDX SELECT {[ ],[ ]} ON , FROM [ ] WHERE ([ ]) 128 PS. COLUMNS(0) ROWS(1) PAGES(2) SECTIONS(3) CHAPTERS(4) jeff@fallever.com
- 45. | | | | | jeff@fallever.com
- 47. ? ETL ? ? OLAP ? ? jeff@fallever.com
- 49. BI BIRT jeff@fallever.com
- 50. Introduction to data cube http://www2.cs.uregina.ca/~dbd/cs831/notes/dcubes/dcubes.html Rapid Miner http://rapid-i.com/content/view/181/90/ SpagoBI http://www.spagoworld.org/xwiki/bin/view/SpagoBI/ Jasperreports http://jasperforge.org/projects/jasperreports pentaho 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_tools jeff@fallever.com
- 52. Bio: &Twitter: @jeff_kit jeff@fallever.com jeff@fallever.com