Uploaded by Akram Nakhaei

BI

advertisement
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫ﻣﻄﺎﻟﻌﻪ ﮔﺮﻭﻫﻲ‬
‫ﮔﺮﻭﻩ ﺩﺍﻧﺸﺠﻮﻳﻲ ﻓﺮﻓﺎ‬
‫ﺩﺭﺱ ‪ :‬ﺍﺻﻮﻝ ﻓﻨﺎﻭﺭﻱ ﺍﻃﻼﻋﺎﺕ‬
‫ﺍﺳﺘﺎﺩ ﺩﺭﺱ‪ :‬ﻣﻬﻨﺪﺱ ﺍﺑﻄﺤﻲ‬
‫ﺩﺍﻧﺸﮕﺎﻩ ﺻﻨﻌﺘﻲ ﺷﺮﻳﻒ‬
‫ﭘﺎﻳﻴﺰ ‪92‬‬
‫‪1‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓﻬﺮﺳﺖ‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫‪2‬‬
‫ﺗﻌﺮﻳﻒ ﺳﺎﻣﺎﻧﻪ ﻫﻮﺷﻤﻨﺪ‬
‫ﺳﺎﺧﺘﺎﺭ ‪BI‬‬
‫ﺗﻌﺮﻳﻒ ﻫﻮﺵ ﺗﺠﺎﺭﻱ )‪(BI‬‬
‫ﻣﻌﻤﺎﺭﻱ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫ﻣﺪﻝﻫﺎﻱ ﺑﻠﻮﻍ‬
‫ﺑﺮﻧﺎﻣﻪﺭﻳﺰﻱ ﺍﺳﺘﺮﺍﺗﮋﻳﻚ ﻭ ﻣﺪﻳﺮﻳﺖ ﻋﻤﻠﻜﺮﺩ ﻛﺴﺐ ﻭ ﻛﺎﺭ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺍﺯ ﺩﻳﺪﮔﺎﻫﻬﺎﻱ ﻣﺨﺘﻠﻒ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫• ﺩﻻﻳﻞ ﺩﺍﺷﺘﻦ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﻣﺒﺘﻨﻲ ﺑﺮ ‪BI‬‬
‫ﺍﻫﺪﺍﻑ ‪BI‬‬
‫•‬
‫• ﺍﺟﺰﺍﻱ ‪BI‬‬
‫•‬
‫•‬
‫•‬
‫‪3‬‬
‫ﺗﻜﻨﻴﻚ ﻫﺎﻱ ﺍﺳﺘﻔﺎﺩﻩ ﺷﺪﻩ ﺩﺭ ‪BI‬‬
‫ﻧﻘﺸﺔ ﺭﺍﻩ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫ﻣﺮﺍﺟﻊ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺳﺎﻣﺎﻧﻪﻫﺎﻱ ﻫﻮﺷﻤﻨﺪ‬
‫•‬
‫•‬
‫•‬
‫‪4‬‬
‫ﻫﻮﺷﻤﻨﺪﻱ‪ ،‬ﻗﺎﺑﻠﻴﺖ ﺩﻧﺒﺎﻝ ﻛﺮﺩﻥ ﻫﺪﻑ ﺑﻪ ﻫﻤﺎﻥ ﺭﻭﺷﻲ ﺍﺳﺖ‪ ،‬ﻛﻪ ﺍﻧﺴﺎﻥ ﺩﻧﺒﺎﻝ ﻣﻲ ﻛﻨﺪ‪.‬‬
‫ﻳﻚ ﺳﺎﻣﺎﻧﻪ ﻫﺮﭼﻪ ﺑﻪ ﺍﻧﺴﺎﻥ ﻧﺰﺩﻳﻜﺘﺮ ﺑﺎﺷﺪ‪ ،‬ﻫﻮﺷﻤﻨﺪﺗﺮ ﺍﺳﺖ‪.‬‬
‫ﺳﺎﻣﺎﻧﻪ ﻫﻮﺷﻤﻨﺪ‪ ،‬ﺳﺎﻣﺎﻧﻪﺍﻱ ﺍﺳﺖ ﻛﻪ ﻫﺪﻑ ﻣﺸﺨﺼﻲ ﺭﺍ ﺑﺎ ﻛﻤﻚ ﺣﺴﮕﺮ ﻭ ﻋﻤﻠﮕﺮ ﺗﺎ‬
‫ﺣﺼﻮﻝ ﻣﻮﻓﻘﻴﺖ ﺩﻧﺒﺎﻝ ﻣﻲ ﻧﻤﺎﻳﺪ‪.‬‬
‫•‬
‫ﺳﺎﻣﺎﻧﻪ ﻫﻮﺷﻤﻨﺪ‪ ،‬ﻣﻲ ﺗﻮﺍﻧﺪ ﺩﺍﻧﺶ ﺧﻮﺩ ﺭﺍ ﺑﺎ ﻳﺎﺩﮔﻴﺮﻱ‪ ،‬ﺍﺯ ﻃﺮﻳﻖ ﺗﺠﺮﺑﻪ ﻭﻳﺎ ﻛﺴﺐ ﺩﺍﻧﺶ‬
‫ﻫﺎﻱ ﺟﺪﻳﺪ ﺍﻓﺰﺍﻳﺶ ﺩﻫﺪ‪.‬‬
‫•‬
‫‪ BI‬ﺑﺎﻳﺪ ﻳﻚ ﺳﺎﻣﺎﻧﻪ ﻫﻮﺷﻤﻨﺪ ﺑﺎﺷﺪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺳﺎﺧﺘﺎﺭ ‪BI‬‬
‫‪BI‬‬
‫ﺍﺑﺰﺍﺭ‬
‫ﺍﺑﺰﺍﺭ ﺗﮑﻨﻴﮏ �ﺎﺭ�ﺮﺩ‬
‫‪5‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺗﮑﻨﻴﮏ‬
‫�ﺎﺭ�ﺮﺩ‬
‫ﺍﺑﺰﺍﺭ ﺗﮑﻨﻴﮏ �ﺎﺭ�ﺮﺩ‬
‫ﻓهﺮﺳﺖ‬
‫ﺗﻌﺮﻳﻒ ﻫﻮﺵ ﺗﺠﺎﺭﻱ )‪(1‬‬
‫•‬
‫ﻋﺒﺎﺭﺗﺴﺖ ﺍﺯ ﺑ‪‬ﻌﺪ ﻭﺳﻴﻌﻲ ﺍﺯ ﻛﺎﺭﺑﺮﺩﻫﺎ ﻭ ﻓﻨﺎﻭﺭﻱ ﺑﺮﺍﻱ ﺟﻤﻊ ﺁﻭﺭﻱ ﺩﺍﺩﻩ ﻭ ﺩﺍﻧﺶ ﺟﻬﺖ‬
‫ﺗﻮﻟﻴﺪ ﭘﺮﺱﻭﺟﻮ ﺩﺭ ﺭﺍﺳﺘﺎﻱ ﺗﺤﻠﻴﻞ ﺑﻨﮕﺎﻩ ﺑﺮﺍﻱ ﺍﺗﺨﺎﺫ ﺗﺼﻤﻴﺎﺕ ﺗﺠﺎﺭﻱ ﺩﻗﻴﻖ ﻭ ﻫﻮﺷﻤﻨﺪ‪.‬‬
‫]‪[Paul Balacky & Richard Fayers, 2003‬‬
‫‪6‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺗﻌﺮﻳﻒ ﻫﻮﺵ ﺗﺠﺎﺭﻱ )‪(2‬‬
‫•‬
‫ﻳﻚ ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺑﺮﺍﺳﺎﺱ ﻳﻚ ﻣﻌﻤﺎﺭﻱ ‪ Enterprise‬ﺗﺸﻜﻴﻞ ﺷﺪﻩ ﻭ ﺩﺭ ﻗﺎﻟﺐ‬
‫‪) OLAP‬ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮﺧﻂ(‪ ،‬ﺑﻪ ﺗﺤﻠﻴﻞ ﺩﺍﺩﻩ ﻫﺎﻱ ﺗﺠﺎﺭﻱ ﻭ ﺍﺗﺨﺎﺫ ﺗﺼﻤﻴﻤﺎﺕ‬
‫ﺩﻗﻴﻖ ﻭ ﻫﻮﺷﻤﻨﺪ ﻣﻲ ﭘﺮﺩﺍﺯﺩ‪[Loshin David, 2003].‬‬
‫‪7‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺗﻌﺮﻳﻒ ﻫﻮﺵ ﺗﺠﺎﺭﻱ )‪(3‬‬
‫‪BI‬‬
‫‪8‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫‪OLTP‬‬
‫‪+‬‬
‫‪OLAP‬‬
‫ﻓهﺮﺳﺖ‬
‫ﺗﻌﺮﻳﻒ ﻫﻮﺵ ﺗﺠﺎﺭﻱ )‪(4‬‬
‫•‬
‫‪9‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﻧﻪ ﺑﻌﻨﻮﺍﻥ ﻳﻚ ﻣﺤﺼﻮﻝ ﻭ ﻧﻪ ﺑﻌﻨﻮﺍﻥ ﻳﻚ ﺳﺎﻣﺎﻧﻪ‪ ،‬ﺑﻠﻜﻪ ﺑﻌﻨﻮﺍﻥ ﻳﻚ ﻣﻌﻤﺎﺭﻱ‬
‫ﻣﻮﺭﺩﻧﻈﺮ ﺍﺳﺖ ﻛﻪ ﺷﺎﻣﻞ ﻣﺠﻤﻮﻋﻪ ﺍﻱ ﺍﺯ ﺑﺮﻧﺎﻣﻪ ﻫﺎﻱ ﻛﺎﺭﺑﺮﺩﻱ ﻭ ﺗﺤﻠﻴﻠﻲ ﺍﺳﺖ ﻛﻪ ﺑﻪ‬
‫ﺍﺳﺘﻨﺎﺩ ﭘﺎﻳﮕﺎﻩ ﻫﺎﻱ ﺩﺍﺩﻩ ﻋﻤﻠﻴﺎﺗﻲ ﻭ ﺗﺤﻠﻴﻠﻲ ﺑﻪ ﺍﺧﺬ ﻭ ﻛﻤﻚ ﺑﻪ ﺍﺧﺬ ﺗﺼﻤﻴﻢ ﺑﺮﺍﻱ ﻓﻌﺎﻟﻴﺖ‬
‫ﻫﺎﻱ ﻫﻮﺷﻤﻨﺪ ﺗﺠﺎﺭﻱ ﻣﻲ ﭘﺮﺩﺍﺯﻧﺪ‪[Larissa T. Moss, Shaku Atre , 2005].‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺳﻴﺮﺗﻜﺎﻣﻞ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫‪DSS‬‬
‫‪EIS‬‬
‫‪BI‬‬
‫‪10‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻣﻌﻤﺎﺭﻱ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫‪11‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻣﺪﻝ ﻫﺎﻱ ﺑﻠﻮﻍ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫•‬
‫ﺍﺑﻌﺎﺩ ﺍﻳﻦ ﻣﺪﻝ ﻧﻴﺰ ﻋﺒﺎﺭﺗﻨﺪ ﺍﺯ ‪:‬‬
‫‪ -1‬ﻣﺤﺪﻭﺩﻩ‪ -2 ،‬ﺣﺎﻣﻴﺎﻥ‪ -3 ،‬ﺗﺎﻣﻴﻦ ﺑﻮﺩﺟﻪ‪ -4 ،‬ﺍﺭﺯﺵ‪-5 ،‬‬
‫ﻫﻮﺵ‬
‫ﻧﻈﺮ ﺑﻠﻮﻍ‬
‫ﺁﻧﻬﺎ ﺍﺯ‬
‫ﺗﻌﻴﻴﻦ‬
‫ﺳﺎﺯﻣﺎﻥ‬
‫ﺍﻣﻜﺎﻥ ﻣﻘﺎﻳﺴﻪ‬
‫ﻛﺎﺭﺑﺮﺍﻥ‬
‫ﺍﺭﺍﺋﻪ ﺑﻪ‬
‫ﺟﺎﻳﮕﺎﻩ‪-8‬‬
‫ﺗﻮﺳﻌﻪ‪،‬‬
‫ﺩﺍﺩﻩ‪،‬ﻫﺎ‪-7‬‬
‫ﺑﻴﻦ‪-6‬‬
‫ﻣﻌﻤﺎﺭﻱ‪،‬‬
‫ﺗﺠﺎﺭﻱ‬
‫•‬
‫ﻧﺤﻮﻩ ﻱ ﺭﺳﻴﺪﻥ ﺑﻪ ﺳﻄﻮﺡ ﺑﺎﻻﺗﺮ ﺑﻠﻮﻍ ﺭﺍ ﺑﻪ ﺳﺎﺯﻣﺎﻧﻬﺎ ﻧﺸﺎﻥ ﻣﻲ ﺩﻫﺪ ﻭ‬
‫ﻣﺴﻴﺮ ﭘﻴﺸﺮﻓﺖ ﺁﻧﻬﺎ ﺭﺍ ﻣﺸﺨﺺ ﻣﻲ ﻛﻨﻨﺪ‪.‬‬
‫•‬
‫•‬
‫•‬
‫•‬
‫ﻣﺪﻝ ﺑﻠﻮﻍ ﺍﻃﻼﻋﺎﺕ ﺗﺠﺎﺭﻱ‬
‫‪12‬‬
‫ﻣﺪﻝ ﺑﻠﻮﻍ ﮔﺎﺭﺗﻨﺮ ﺑﺮﺍﻱ ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﻭ ﺍﺭﺯﻳﺎﺑﻲ ﻋﻤﻠﻜﺮﺩ‬
‫ﻣﺪﻝ ﺑﻠﻮﻍ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪/‬ﻣﺪﻳﺮﻳﺖ ﻋﻤﻠﻜﺮﺩ ﻣﺆﺳﺴﻪ ﺗﺤﻘﻴﻘﺎﺗﻲ ‪AMR‬‬
‫‪TDWI‬‬
‫ﻣﺪﻝ ﺑﻠﻮﻍ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺑﺮﻧﺎﻣﻪ ﺭﻳﺰﻱ ﺍﺳﺘﺮﺍﺗﮋﻳﻚ ﻭ ﻣﺪﻳﺮﻳﺖ ﻋﻤﻠﻜﺮﺩ‬
‫ﻛﺴﺐ ﻭﻛﺎﺭ‬
‫•‬
‫ﺑﺮﻧﺎﻣﻪ ﺭﻳﺰﻱ ﺍﺳﺘﺮﺍﺗﮋﻳﻚ‬
‫•‬
‫ﻛﺴﺐ ﻭﻛﺎﺭ‪ ،‬ﺳﻨﺠﻪ ﻫﺎ‪ ،‬ﻓﺮﺍﻳﻨﺪﻫﺎ ﻭ ﺳﻴﺴﺘﻢ ﻫﺎ ﺑﺮﺍﻱ ﺍﺳﺘﺨﺮﺍﺝ ﻋﻤﻠﻜﺮﺩ ﺳﺎﺯﻣﺎﻥ ﻣﻲ ﺑﺎﺷﺪ ﻭ ﺑﻪ ﺳﺎﺯﻣﺎﻥ ﻫﺎ‬
‫ﻣﺪﻳﺮﻳﺖ ﻋﻤﻠﻜﺮﺩ ﻛﺴﺐ ﻭﻛﺎﺭ )‪ (BPM‬ﻭ ﻳﺎ ﻣﺪﻳﺮﻳﺖ ﻋﻤﻠﻜﺮﺩ‬
‫ﻛﻤﻚ ﻣﻲ ﻛﻨﺪ ﺗﺎ ﻣﺠﻤﻮﻋﻪ ﺍﻱ ﻣﻨﺴﺠﻢ ﺍﺯ ﺍﻫﺪﺍﻑ ﺭﺍ ﺑﻪ ﺑﺮﻧﺎﻣﻪ ﻫﺎ ﺗﺮﺟﻤﻪ ﻧﻤﺎﻳﺪ‪ ،‬ﺑﺮ ﺍﺟﺮﺍ ﻧﻈﺎﺭﺕ ﻧﻤﺎﻳﺪ ﻭ ﺩﺭ‬
‫ﺳﺎﺯﻣﺎﻥ)‪: (CPM‬‬
‫ﺭﺍﺳﺘﺎﻱ ﺑﻬﺒﻮﺩ ﻋﻤﻠﻜﺮﺩ ﻣﺎﻟﻲ ﻭ ﻋﻤﻠﻴﺎﺗﻲ ﺑﻴﻨﺶ ﺍﺭﺍﺋﻪ ﻧﻤﺎﻳﺪ‪".‬‬
‫• ﻓﺮﺍﻳﻨﺪﻱ ﺩﺭ ﺭﺍﺳﺘﺎﻱ ﻓﺮﻣﻮﻟﻪ ﻧﻤﻮﺩﻥ ﻭ ﺗﺸﺮﻳﺢ ﺍﺳﺘﺮﺍﺗﮋﻱ ﻫﺎﻱ ﺳﺎﺯﻣﺎﻧﻲ ﻭ ﺍﺗﺼﺎﻝ ﺁﻥ‬
‫ﺳﺎﺯﻣﺎﻥ ﻫﺎ‬
‫ﺍﺳﺘﺮﺍﺗﮋﻱ ﺩﺭ‬
‫ﺑﺮﺍﻱﺳﺎﺯﻱ‬
‫ﭼﺎﺭﭼﻮﺑﻲﭘﻴﺎﺩﻩ‬
‫ﻭﻛﺎﺭ‪،‬ﻧﺤﻮﻩ ﻱ‬
‫ﻧﻈﺎﺭﺕ ﺑﺮ‬
‫ﻋﻤﻠﻴﺎﺕ ﻭ‬
‫" ﺑﻪ‬
‫ﺗﺤﻠﻴﻞ ﻣﺘﺪﻭﻟﻮژﻱ ﻫﺎﻱ‬
‫ﻣﻜﺎﻧﻴﺰﻩ ﻛﺮﺩﻥ ﻭ‬
‫ﺳﺎﺯﻣﺎﻧﺪﻫﻲ‪،‬‬
‫ﻋﻤﻠﻜﺮﺩ ﻛﺴﺐ‬
‫ﻣﺪﻳﺮﻳﺖ‬
‫ﻣﺎﻟﻲ‬
‫•‬
‫‪13‬‬
‫ﻛﺎﺭﺕ‬
‫ﺍﻣﺘﻴﺎﺯﻱ‬
‫ﻣﺘﻮﺍﺯﻥ‬
‫ﻓﺮﺍﻳﻨﺪ‬
‫ﻣﺸﺘﺮﻱ‬
‫ﻣﺘﻮﺍﺯﻥ‪(BSC) Balanced -‬‬
‫ﻛﺎﺭﺕ ﺍﻣﺘﻴﺎﺯﻱ‬
‫ﻳﻜﻲ ﺍﺯ ﭘﺮﻛﺎﺭﺑﺮﺩﺗﺮﻳﻦ ﺁﻥ ﻫﺎ ﭼﺎﺭﭼﻮﺏ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫‪Scorecard‬‬
‫ﻓﺮﻓﺎ‬
‫ﺭﺷﺪ ﻭ‬
‫ﻳﺎﺩﮔﻴﺮﻱ‬
‫ﻣﺪﻝ ﻫﺎﻱ ﺑﻠﻮﻍ ﻣﺪﻳﺮﻳﺖ ﺍﺳﺘﺮﺍﺗﮋﻳﻚ‬
‫ﺍﺑﻌﺎﺩ ﺍﻳﻦ ﻣﺪﻝ ﻧﻴﺰ ﻋﺒﺎﺭﺗﻨﺪ ﺍﺯ ‪ -1 :‬ﺭﻫﺒﺮﻱ‪ -2 ،‬ﻓﺮﻫﻨﮓ ﻫﺎ ﻭ‬
‫ﺍﺭﺯﺵ ﻫﺎ‪-3 ،‬ﺗﻔﻜﺮ ﻭ ﺑﺮﻧﺎﻣﻪ ﺭﻳﺰﻱ ﺍﺳﺘﺮﺍﺗﮋﻳﻚ‪ -4 ،‬ﻫﻤﺴﻮﻳﻲ‪،‬‬
‫‪ -5‬ﺍﻧﺪﺍﺯﻩﮔﻴﺮﻱ ﻋﻤﻠﻜﺮﺩ‪-6 ،‬ﻣﺪﻳﺮﻳﺖ ﻋﻤﻠﻜﺮﺩ‪ -7 ،‬ﺑﻬﺒﻮﺩ‬
‫ﻓﺮﺍﻳﻨﺪ‪ -8 ،‬ﭘﺎﻳﺪﺍﺭﻱ ﻣﺪﻳﺮﻳﺖ ﺍﺳﺘﺮﺍﺗﮋﻳﻚ‪.‬‬
‫•‬
‫ﺗﺎﻛﻨﻮﻥ ﻣﺪﻝ ﻫﺎﻱ ﺑﻠﻮﻍ ﺯﻳﺎﺩﻱ ﺩﺭ ﺣﻮﺯﻩ ﻱ ﻣﺪﻳﺮﻳﺖ ﺍﺳﺘﺮﺍﺗﮋﻳﻚ ﻭ ﺑﺮﻧﺎﻣﻪ ﺭﻳﺰﻱ‬
‫ﻋﻤﻠﻜﺮﺩ ﻛﺴﺐ ﻭﻛﺎﺭ ﺗﻮﺳﻌﻪ ﻭ ﻛﺎﺭﺑﺮﺩﻱ ﻧﺸﺪﻩ ﺍﻧﺪ ﻭ ﺷﺎﻳﺪ ﺑﺘﻮﺍﻥ ﺗﻨﻬﺎ‬
‫ﺍﺳﺘﺮﺍﺗﮋﻳﻚ ﻭ ﻣﺪﻳﺮﻳﺖ‬
‫ﺳﻄﺢ ‪: 5‬‬
‫ﺑﻬﺒﻮﺩ ﻣﺪﺍﻭﻡ‬
‫ﺳﻄﺢ ‪4‬‬
‫ﻣﺪﻝ‪:‬ﺷﺪﻩﺑﻠﻮﻍ ﻣﺪﻳﺮﻳﺖ ﺍﺳﺘﺮﺍﺗﮋﻳﻚ ﺩﺍﻧﺴﺖ ﻛﻪ ﺗﻮﺳﻂ‬
‫ﺭﺍ‬
‫ﺣﻮﺯﻩ‬
‫ﻣﺪﻝ ﻣﻄﺮﺡ ﻭ ﺑﻪ ﺭﻭﺯ ﺍﻳﻦ‬
‫ﻣﺪﻳﺮﻳﺖ‬
‫ﺳﻄﺢ ‪: 3‬‬
‫ﻣﻮﺳﺴﻪ ﻛﺎﺭﺕ ﺍﻣﺘﻴﺎﺯﻱ ﻣﺘﻮﺍﺯﻥ ﻭ‬
‫ﺍﺳﺖ‪.‬‬
‫ﻣﺘﻤﺮﻛﺰﺩﺍﺩﻩ ﺷﺪﻩ‬
‫ﺗﻮﺳﻌﻪ‬
‫ﺳﺎﺧﺘﻴﺎﻓﺘﻪ ﻭ‬
‫ﺑﻴﺶ ﻓﻌﺎﻝ‬
‫‪14‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺳﻄﺢ ‪: 2‬‬
‫ﻓﻌﺎﻝ‬
‫ﺳﻄﺢ ‪: 1‬‬
‫ﺍﻳﺴﺘﺎ ﻭ‬
‫ﺍﻗﺘﻀﺎﻳﻲ‬
‫ﻓهﺮﺳﺖ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺍﺯ ﺩﻳﺪﮔﺎﻩ ﻫﺎﻱ ﻣﺨﺘﻠﻒ‬
‫‪‬ﻣﻨﻈﺮ ﻣﺪﻳﺮﻳﺘﻲ‪:‬‬
‫ﺩﺭ ﺍﻳﻦ ﻣﻨﻈﺮ ‪ BI‬ﺩﺍﺭﺍﻱ ﺷﺎﺧﺼﻪ ﻫﺎﻱ ﺯﻳﺮ ﺍﺳﺖ‪:‬‬
‫•‬
‫ﺗﺼﺤﻴﺢ ﻭ ﭘﻴﺎﺩﻩ ﺳﺎﺯﻱ ﻓﺮﺍﻳﻨﺪ ﺗﺼﻤﻴﻢ ﮔﻴﺮﻱ ﻣﺪﻳﺮﺍﻥ ﻛﻪ ﺩﺭ ﺁﻧﻬﺎ ﺩﺍﻧﺸﻲ ﺑﺮ‬
‫ﭘﺎﻳﻪ ﺩﻗﻴﻖ ﺗﺮﻳﻦ ﻭ ﺟﺎﻣﻊ ﺗﺮﻳﻦ ﺍﻃﻼﻋﺎﺕ ﻭﺍﻗﻌﻲ ﺳﺎﺯﻣﺎﻥ‪ ،‬ﺍﻳﺠﺎﺩ ﻣﻲ ﺷﻮﺩ‪.‬‬
‫• ﺍﻓﺰﺍﻳﺶ ﺗﻮﺍﻧﺎﻳﻲ ﻣﺪﻳﺮ ﺩﺭ ﺍﻋﻤﺎﻝ ﺗﺼﻤﻴﻤﺎﺕ ﺍﺳﺘﺮﺍﺗﮋﻳﻚ‪.‬‬
‫‪15‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺍﺯ ﺩﻳﺪﮔﺎﻩ ﻫﺎﻱ ﻣﺨﺘﻠﻒ‬
‫‪‬‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫‪16‬‬
‫ﻣﻨﻈﺮ ﻣﻌﻤﺎﺭﻱ ﻭ ﻓﺮﺍﻳﻨﺪﻫﺎﻱ ﺳﺎﺯﻣﺎﻧﻲ‬
‫ﻳﻚ‪ framework‬ﺍﺳﺖ‪.‬‬
‫ﺑﺴﺘﺮﻱ ﺑﺮﺍﻱ ﺣﺮﻛﺖ ﺍﺯ ﺩﺍﺩﻩ ﺑﻪ ﺍﻃﻼﻋﺎﺕ ﻭ ﺍﺯ ﺍﻃﻼﻋﺎﺕ ﺑﻪ ﺩﺍﻧﺶ ﺑﺎ ﺍﻳﺠﺎﺩ ﺍﺭﺯﺵ‬
‫ﺍﻓﺰﻭﺩﻩ ﺑﺮﺍﻱ ﺳﺎﺯﻣﺎﻥ‪.‬‬
‫ﺗﻤﺮﻛﺰ ﺑﺮ ﻓﺮﺍﻳﻨﺪﻫﺎﻱ ﺗﺼﻤﻴﻢ ﮔﻴﺮﻱ ﺩﺭ ﺳﻄﻮﺡ ﻣﺨﺘﻠﻒ ﻣﺪﻳﺮﻳﺘﻲ ﺩﺭ ﺳﺎﺯﻣﺎﻥ‪.‬‬
‫ﺍﻓﺰﺍﻳﺶ ﻛﺎﺭﺁﻳﻲ ﺳﺎﺯﻣﺎﻥ ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ ﺑﺨﺶ ﻫﺎﻳﻲ ﻣﺎﻧﻨﺪ ﭘﺮﺳﻨﻞ ﻣﺠﺮﺏ‪ ،‬ﺍﻃﻼﻋﺎﺕ‬
‫ﭘﻨﻬﺎﻥ ﺗﺠﺎﺭﻱ‪ ،‬ﻛﺎﻫﺶ ﻓﺮﺍﻳﻨﺪﻫﺎﻱ ﺍﺿﺎﻓﻲ ﻭ‪...‬‬
‫ﺍﺗﺤﺎﺩ ﻭ ﻳﻜﭙﺎﺭﭼﮕﻲ ﻓﺮﺍﻳﻨﺪﻫﺎﻱ ﺳﺎﺯﻣﺎﻥ ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺍﺯ ﺩﻳﺪﮔﺎﻩ ﻫﺎﻱ ﻣﺨﺘﻠﻒ‬
‫‪‬ﻣﻨﻈﺮ ﺑﺎﺯﺍﺭ‪:‬‬
‫•‬
‫•‬
‫•‬
‫•‬
‫ﺍﻳﺠﺎﺩ ﺑﺮﺗﺮﻱ ﺭﻗﺎﺑﺘﻲ ﺑﺎ ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﺍﺑﺰﺍﺭﻫﺎﻱ ﻗﺪﺭﺗﻤﻨﺪ ﺗﺤﻠﻴﻞ ﺭﻗﺒﺎ‪.‬‬
‫ﻧﻈﺎﺭﺕ )‪ (Monitoring‬ﻫﻮﺷﻤﻨﺪ ﺗﻌﺎﻣﻞ ﺑﺎ ﻣﺸﺘﺮﻳﺎﻥ‪ ،‬ﺷﺮﻛﺎﻱ ﺗﺠﺎﺭﻱ )ﻣﺎﻧﻨﺪ‬
‫‪ supplyer‬ﻫﺎ(‪.‬‬
‫ﻧﻈﺎﺭﺕ ﻫﻮﺷﻤﻨﺪ ﺑﺎﺯﺍﺭ ﻭ ﺷﻨﺎﺳﺎﻳﻲ ﺗﻐﻴﻴﺮﺍﺕ ﺁﺗﻲ ﺁﻥ‪.‬‬
‫ﻓﺮﺁﻳﻨﺪ ﺑﺎﻻﺑﺮﺩﻥ ﺳﻮﺩﺩﻫﻲ ﺳﺎﺯﻣﺎﻥ ﺩﺭ ﺑﺎﺯﺍﺭ ﺭﻗﺎﺑﺘﻲ‬
‫‪17‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺍﺯ ﺩﻳﺪﮔﺎﻩ ﻫﺎﻱ ﻣﺨﺘﻠﻒ‬
‫‪‬ﻣﻨﻈﺮ ﻓﻨﺎﻭﺭﻱ‪:‬‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫‪18‬‬
‫ﻳﻚ ﺳﻴﺴﺘﻢ ﻫﻮﺷﻤﻨﺪ‪.‬‬
‫ﺍﻳﺠﺎﺩ ﺑﺴﺘﺮ ﻓﻨﻲ ﻭ ﻣﻌﻤﺎﺭﻱ ﻣﻨﺎﺳﺐ ﺟﻬﺖ ﮔﺴﺘﺮﺵ ﻭ ﺍﺳﺘﻔﺎﺩﻩ ﺑﻬﻴﻨﻪ ﺍﺯ ﻣﻨﺎﺑﻊ‪.‬‬
‫ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﺍﺑﺰﺍﺭﻫﺎﻱ ﻧﺮﻡ ﺍﻓﺰﺍﺭﻱ ﻭ ﺳﺨﺖ ﺍﻓﺰﺍﺭﻱ ﺩﺭ ﺭﺍﺳﺘﺎﻱ ﺷﻨﺎﺳﺎﻳﻲ‪ ،‬ﺟﻤﻊ ﺁﻭﺭﻱ‪،‬‬
‫ﭘﺮﺩﺍﺯﺵ ﻭ ﻧﺘﻴﺠﻪ ﮔﻴﺮﻱ ﻭ ﻧﻤﺎﻳﺶ ﺩﺍﺩﻩ ﻫﺎ ﻭ ﺍﻃﻼﻋﺎﺕ ﻣﻮﺭﺩ ﻧﻴﺎﺯ ﺩﺭ ﺳﺎﺯﻣﺎﻥ‪.‬‬
‫ﻣﺒﺘﻨﻲ ﺑﺮ ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﻫﺎﻱ ﺑﺰﺭﮔﻲ ﻣﺎﻧﻨﺪ ‪ data ware house‬ﻭ ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﻫﺎﻱ‬
‫ﻋﻤﻠﻴﺎﺗﻲ‪.‬‬
‫ﺩﺭ ﺗﻌﺎﻣﻞ ﺑﺎ ﺑﺴﻴﺎﺭﻱ ﺍﺯ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﻛﺎﻣﭙﻴﻮﺗﺮﻱ ﺩﻳﮕﺮ‪.‬‬
‫ﻣﺒﺘﻨﻲ ﺑﺮ ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮ ﺧﻂ )‪.(OLAP‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺩﻻﻳﻞ ﺭﻭﺁﻭﺭﻱ ﺑﻪ ‪BI‬‬
‫ﻣﺪﻳﺮﻳﺖ‬
‫ﺳﺎﺯﻣﺎﻧﻬﺎ‬
‫ﺑﺎﺯﺍﺭ‬
‫ ﭘﻴﭽﻴﺪﮔﻲ ﻣﺪﻳﺮﻳﺖ‬‫ ﺑﺎﺯﺍﺭ ﺑﻪ ﺷﺪﺕ ﺭﻗﺎﺑﺘﻲ ‪-‬ﺍﺭﮔﺎﻧﻬﺎ ﺑﺮ ﺍﺳﺎﺱ‬‫ﺍﻃﻼﻋﺎﺕ ﺑﺎ ﻫﻢ ﺭﻗﺎﺑﺖ ﺍﻓﺰﺍﻳﺶ ﻳﺎﻓﺘﻪ ﺍﺳﺖ‪.‬‬
‫ﺷﺪﻩ ﻭ ﻧﻮﺁﻭﺭﻱﻫﺎ ﻭ‬
‫ﻣﻲ ﻛﻨﻨﺪ ﻭ ﺯﻣﺎﻥ ﺑﺮﺍﻱ ﺍﻣﺮﻭﺯﻩ ﺣﺘﻲ ﺷﺮﻛﺘﻬﺎﻱ‬
‫ﺍﺑﺘﻜﺎﺭﺍﺕ ﻫﺮ ﺭﻭﺯ‬
‫ﻛﻮﭼﻚ ﻧﻴﺰ ﺑﺼﻮﺭﺕ‬
‫ﺑﺪﺳﺖ ﺁﻭﺭﻱ ﺍﻳﻦ‬
‫ﺍﻓﺰﺍﻳﺶ ﻣﻲ ﻳﺎﺑﺪ‪.‬‬
‫ﺍﻃﻼﻋﺎﺕ ﻣﺤﺪﻭﺩ ﺍﺳﺖ‪ .‬ﺑﻴﻦ ﺍﻟﻤﻠﻠﻲ ﻛﺎﺭ‬
‫ﻣﻴﻜﻨﻨﺪ‪.‬‬
‫ﻓهﺮﺳﺖ‬
‫‪19‬‬
‫ﺑﺮ�� ﺍﺯ�ﺎﺭ�ﺮﺩهﺎی ﺑﺮﻧﺎﻣﻪ هﺎی ﺗﺼﻤﻴﻢ ﻳﺎﺭ ‪BI‬‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫‪20‬‬
‫ﺗﺤﻠﻴﻞ ﭼﻨﺪ ﺑﻌﺪﻱ ﺍﺯﺩﺍﺩﻩ ﻫﺎﻱ ﻋﻤﻠﻴﺎﺗﻲ ﺩﺭ ﻗﺎﻟﺐ ‪،OLAP‬‬
‫ﺩﺍﺩﻩ ﻛﺎﻭﻱ‪،‬‬
‫ﭘﻴﺶ ﺑﻴﻨﻲ ﻛﺮﺩﻥ‪،‬‬
‫ﺗﺤﻠﻴﻞ ﺗﺠﺎﺭﻱ‪،‬‬
‫ﭘﺮﺱ ﻭﺟﻮ ﻛﺮﺩﻥ ﻭ ﮔﺰﺍﺭﺵ ﮔﻴﺮﻱ ﻭ ﺗﺮﺳﻴﻢ ﺁﻣﺎﺭﻱ‪،‬‬
‫ﺗﺤﻠﻴﻞ ﻣﻜﺎﻧﻲ‪،‬‬
‫ﻣﺪﻳﺮﻳﺖ ﺩﺍﻧﺶ‪،‬‬
‫ﻛﺎﻭﺵ ﺩﺭ ﻣﺘﻦ‪ ،‬ﻣﺤﺘﻮﺍ ﻭ ﺻﻮﺕ‪،‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺩﻻﻳﻞ ﺩﺍﺷﺘﻦ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﻣﺒﺘﻨﻲ ﺑﺮ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫‪21‬‬
‫ﺩﻻﻳﻞ ﺍﻗﺘﺼﺎﺩﻱ‪.‬‬
‫ﺩﻧﺒﺎﻝ ﻧﻤﻮﺩﻥ ﺍﻫﺪﺍﻑ ﻛﺎﺭﺍﻳﻲ ﺳﺎﻣﺎﻧﻪ ﻛﺎﺭﺑﺮﺩﻱ‪.‬‬
‫ﺍﻓﺰﺍﻳﺶ ﺭﻗﺎﺑﺖ ﻫﺎ‪.‬‬
‫ﺗﺠﺎﺭﺕ ﺍﻟﻜﺘﺮﻭﻧﻴﻜﻲ‬
‫ﺣﻤﺎﻳﺖ ﺍﺯ ﺗﺼﻤﻴﻢ ﮔﻴﺮﻱ ﻫﺎﻱ ﺳﺎﻣﺎﻧﻪ ﻛﺎﺭﺑﺮﺩﻱ‪.‬‬
‫ﻛﺜﺮﺕ ﻣﺸﺘﺮﻳﺎﻥ‪.‬‬
‫ﻧﻴﺎﺯ ﺑﻪ ﺗﺤﻠﻴﻞ ﻋﻤﻠﻴﺎﺕ ﺳﻴﺴﺘﻢ‪.‬‬
‫ﺻﺤ‪‬ﺖ ﻭ ﺩﻗّﺖ ﺍﻃّﻼﻋﺎﺕ ﺣﺎﺻﻞ ﺍﺯ ﺳﺎﻣﺎﻧﻪ‪.‬‬
‫ﺩﺳﺘﺮﺳﻲ ﺑﻪ ﺩﺍﺩﻩ ﻫﺎﻱ ﺑﻬﻨﮕﺎﻡ ﺷﺪﻩ‪.‬‬
‫ﻛﺎﻫﺶ ﻫﺰﻳﻨﻪ‪.‬‬
‫ﺭﺿﺎﻳﺖ ﻛﺎﺭﺑﺮﺍﻥ ﻧﻬﺎﻳﻲ ﺩﺭ ﻣﻘﺎﻳﺴﻪ ﺑﺎ ﻛﺎﻻﻫﺎﻱ ﻣﺸﺎﺑﻪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺍهﺪﺍﻑ ‪BI‬‬
‫•‬
‫ﺍﻧﺘﻈﺎﺭ ﺩﺍﺭﻳﻢ ﻛﻪ ﻳﻚ ﺳﺎﻣﺎﻧﻪ ‪ ،BI‬ﺗﺤﻠﻴﻞ ﺩﺍﺩﻩ ﺭﺍ ﺑﻪ ﻛﻤﻚ ﺗﺤﻠﻴﻞ ﺁﻣﺎﺭﻱ ﻭ ﺑﺮ ﻣﺒﻨﺎﻱ ﻳﻚ‬
‫ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴﻠﻲ ﻣﻴﺴ‪‬ﺮ ﺳﺎﺯﺩ‬
‫ﺗﺤﻠﯿﻞ ﺩﺍﺩﻩ‬
‫‪22‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﭘﺎﻳ�ﺎﻩ ﺩﺍﺩﻩ‬
‫ﺗﺤﻠﻴ��‬
‫ﺗﺤﻠﯿﻞ ﺁﻣﺎﺭی‬
‫ﻓهﺮﺳﺖ‬
‫ﺍﺟﺰﺍﻱ ‪BI‬‬
‫‪23‬‬
‫•‬
‫ﻛﺎﺭﺑﺮﺍﻥ‬
‫•‬
‫•‬
‫•‬
‫ﻣﺤﺼﻮﻝ‬
‫ﺧﺪﻣﺎﺕ ﻗﺎﺑﻞ ﺍﺭﺍﺋﻪ‬
‫ﺭﻗﺒﺎ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺗﻜﻨﻴﻚ ﻫﺎﻱ ﺍﺳﺘﻔﺎﺩﻩ ﺷﺪﻩ ﺩﺭ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
•
•
•
•
•
•
•
•
•
•
•
On-Line Analytical Processing (OLAP)
On-Line Transaction Processing (OLTP)
Data Warehousing (DW)
Data Mining (DM)
Intelligent Decision Support System (IDSS)
Intelligent Agent (IA)
Knowledge Management System (KMS)
Supply Chain Management (SCM)
Customer Relationship Management (CRM)
Enterprise Resource Planing (ERP)
Enterprise Information Management (EIM)
‫ﻓهﺮﺳﺖ‬
‫ ﮔﺮﻭﻩ‬،‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫ﻓﺮﻓﺎ‬
24
‫ﺗﮑﻨﻴﮏ هﺎی ﺍﺳﺘﻔﺎﺩﻩ ﺷﺪﻩ ﺩﺭ هﻮﺵ ﺗﺠﺎﺭی)ﺍﺩﺍﻣﻪ(‬
‫ﻟﻱﺴﺖ ﺍﻣﻮﺍﻝ‬
‫ﻓﺮﻭﺵ‬
‫‪EIM‬‬
‫‪CRM‬‬
‫ﺗﻮﺯﻱﻊ‬
‫‪DM‬‬
‫‪ERP‬‬
‫‪DB‬‬
‫‪KMS‬‬
‫‪DW‬‬
‫‪OLAP OLTP‬‬
‫‪IDSS‬‬
‫‪SCM‬‬
‫ﻗﻴﻤﺖ ﮔﺬﺍﺭی ﻣﺤﺼﻮﻝ‬
‫‪25‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫)‪OLAP (On-Line Analytical Processing‬‬
‫•‬
‫ﺳﺮﻭﻳﺲ ﻫﺎﻳﻲ ﻛﻪ ﺍﺯ ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴﻠﻲ ﺑﻪ ﻣﻨﻈﻮﺭ ﭘﺎﺳﺨﮕﻮﻳﻲ ﺳﺮﻳﻊ ﺑﻪ ﭘﺮﺳﺶ ﻫﺎﻱ‬
‫ﺗﺤﻠﻴﻠﻲ ﻛﺎﺭﺑﺮﺍﻥ ﺍﺳﺘﻔﺎﺩﻩ ﻣﻲ ﻛﻨﻨﺪ‪ ،‬ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮﺧﻂ )‪ (OLAP‬ﻧﺎﻣﻴﺪﻩ ﻣﻲ ﺷﻮﻧﺪ‪.‬‬
‫•‬
‫‪ OLAP‬ﻋﺒﺎﺭﺕ ﺍﺳﺖ ﺍﺯ ﻣﺠﻤﻮﻋﻪ ﺍﻱ ﺍﺯ ﻧﺮﻡ ﺍﻓﺰﺍﺭﻫﺎ ﻛﻪ ﺑﺮﺍﻱ ﺍﻛﺘﺸﺎﻑ ﻭ ﺗﺤﻠﻴﻞ ﺳﺮﻳﻊ ﺩﺍﺩﻩ‬
‫ﻫﺎﻱ ﻣﺒﺘﻨﻲ ﺑﺮ ﻳﻚ ﺷﻴﻮﺓ ﭼﻨﺪ ﺑ‪‬ﻌﺪﻱ ﺑﺎ ﭼﻨﺪﻳﻦ ﺳﻄﺢ ﺍﺯ ﻣﺠﻤﻮﻉ ﺳﺎﺯﻱ ﺍﺳﺘﻔﺎﺩﻩ ﻣﻲ ﺷﻮﺩ‪.‬‬
‫)‪ ،(Aggregation‬ﺗﺼﻤﻴﻢ ﮔﻴﺮﻱ ﺭﺍ ﺳﺮﻳﻊ ﻭ ﺁﺳﺎﻥ ﻣﻲ ﻛﻨﺪ‪.‬‬
‫•‬
‫ﺁﺳﺎﻥ ﺷﺪﻥ ﺗﺼﻤﻴﻢ ﮔﻴﺮﻱ ﺑﻪ ﺩﻟﻴﻞ ﻗﺎﺑﻠﻴﺖ ﻫﺪﺍﻳﺖ ﺗﺤﻠﻴﻞ ﻫﺎ ﺑﺪﻭﻥ ﻧﻴﺎﺯ ﺑﻪ ﻳﻚ ﺯﺑﺎﻥ‬
‫ﭘﺮﺱ ﻭ ﺟﻮﻱ ﺍﺻﻠﻲ ﻳﺎ ﻓﻬﻢ ﺳﺎﺧﺘﺎﺭ ﺯﻳﺮﻳﻦ ﺑﺎﻧﻚ ﺍﻃﻼﻋﺎﺗﻲ ﺣﺎﺻﻞ ﻣﻲ ﺷﻮﺩ‪.‬‬
‫‪26‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫‪) OLAP‬ﺍﺩﺍﻣﻪ(‬
‫‪27‬‬
‫•‬
‫ﺳﺮﻳﻊ ﺗﺮﺷﺪﻥ ﺗﺼﻤﻴﻢ ﮔﻴﺮﻱ ﻧﻴﺰ ﺍﺯ ﺍﻳﻦ ﺟﻬﺖ ﺍﺳﺖ ﻛﻪ ﻣﺠﻤﻮﻉ ﺩﺍﺩﻩ ﻫﺎ ﺑﺮﺍﻱ ﺩﺭﺧﻮﺍﺳﺖ‬
‫ﻫﺎﻱ ﻣﺘﺪﺍﻭﻝ ﺍﺯ ﭘﻴﺶ ﻣﺤﺎﺳﺒﻪ ﺷﺪﻩ ﺍﺳﺖ ﻭ ﺑﻪ ﺍﺻﻄﻼﺡ ﺩﺍﺩﻩ ﻫﺎ‪ Pre-Aggregate ،‬ﺷﺪﻩ‬
‫ﺍﻧﺪ‪ ،‬ﺑﻨﺎﺑﺮﺍﻳﻦ ﺯﻣﺎﻥ ﻣﺤﺎﺳﺒﻪ ﻛﺎﻫﺶ ﻳﺎﻓﺘﻪ ﻭ ﭘﺎﺳﺨﮕﻮﻳﻲ ﺑﻪ ﭘﺮﺱ ﻭﺟﻮﻫﺎﻱ ﭘﻴﭽﻴﺪﺓ ﺗﺤﻠﻴﻠﻲ‬
‫ﺑﻪ ﺳﺮﻋﺖ ﺍﻣﻜﺎﻧﭙﺬﻳﺮ ﺧﻮﺍﻫﺪ ﺑﻮﺩ‪.‬‬
‫•‬
‫ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴﻠﻲ )‪ (DW‬ﻭ ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮ ﺧﻂ )‪ (OLAP‬ﺍﺯ ﺟﻤﻠﻪ ﻋﻨﺎﺻﺮ ﺿﺮﻭﺭﻱ‬
‫ﺩﺭ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﺗﺼﻤﻴﻢ ﻳﺎﺭ ﺑﻪ ﺷﻤﺎﺭ ﻣﻲ ﺁﻳﻨﺪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﻋﻤﻠﻴﺎﺕ ﻣﺘﺪﺍﻭﻝ ﺩﺭ ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴ�� ﺑﺮﺧﻂ‬
‫‪28‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫)‪OLTP (On-Line Transaction Processing‬‬
‫•‬
‫ﺩﺍﺩﻩﻫﺎﻱ ﻣﻮﺭﺩ ﺍﺳﺘﻔﺎﺩﻩ ﺩﺭ ﺍﻳﻦ ﺗﺮﺍﻛﻨﺶﻫﺎ ﺩﺍﺩﻩﻫﺎﻱ ﺑﻪﺭﻭﺯ‪ ،‬ﺟﺎﺭﻱ ﻭ ﺑﺎ ﺟﺰﺋﻴﺎﺕ ﺍﺳﺖ ‪:‬‬
‫ﭘﺮﺩﺍﺯﺵ ﺗﺮﺍﻛﻨﺶﻫﺎ‪ ،‬ﻣﺸﺘﻤﻞ ﺑﺮ ﺍﻧﺠﺎﻡ ﻋﻤﻠﻴﺎﺕ ﺭﻭﺯﺍﻧﻪ ﻣﺎﻧﻨﺪ ﺧﺮﻳﺪ ﻭ ﻓﺮﻭﺵ ﻭ ﻋﻤﻠﻴﺎﺕ‬
‫ﺑﺎﻧﻜﻲ ﻭ ﻣﺎﻧﻨﺪ ﺁﻥ‪.‬‬
‫•‬
‫•‬
‫ﭘﺎﻳﮕﺎﻩ ﻫﺎﻱ ﺩﺍﺩﻩ ﻋﻤﻠﻴﺎﺗﻲ‪ ،‬ﻣﻨﺒﻊ ﺩﺍﺩﻩ ﺍﻱ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ‪ OLTP‬ﻫﺴﺘﻨﺪ‪.‬‬
‫‪29‬‬
‫ﭘﺎﻳﮕﺎﻩ ﻫﺎﻱ ﺩﺍﺩﺓ ﻋﻤﻠﻴﺎﺗﻲ ﺭﺍﻳﺞ ﺷﺎﻣﻞ ﺩﺍﺩﻩ ﻫﺎﻱ ﺑﺮﻭﺯ ﻭ ﺟﺎﺭﻱ‪ ،‬ﺟﻬﺖ ﺍﻧﺠﺎﻡ ﻋﻤﻠﻴﺎﺕ ﺭﻭﺯﺍﻧﺔ‬
‫ﺛﺒﺖ‪ ،‬ﺣﺬﻑ‪ ،‬ﺑﺮﻭﺯﺭﺳﺎﻧﻲ ﻭ ﻣﺸﺎﻫﺪﻩ ﺩﺍﺩﻩ ﻫﺎ ﻫﺴﺘﻨﺪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﻣﻘﺎﻳﺴﻪ ﺟﻨﺒﻪ ﻫﺎﻱ ﻣﺘﻔﺎﻭﺕ ‪OLAP , OLTP‬‬
‫ﺳﻴﺴﺘﻢ ﻫﺎﻱ‬
‫ﻣﻘﺎﻳﺴﻪ ﺷﺪﻩ‬
‫ﭘﺎﺭﺍﻣﺘﺮﻫﺎﻱ‬
‫ﺍﺭﺯﻳﺎﺑﻲ‬
‫ﭘﺮﺩﺍﺯﺵ ﺗﺮﺍﻛﻨﺶ ﺑﺮﺧﻂ )‪(OLTP‬‬
‫ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮﺧﻂ )‪(OLAP‬‬
‫ﻛﺎﺭﺑﺮﺍﻥ ﻓﻨﺎﻭﺭﻱ ﺍﻃﻼﻋﺎﺕ‬
‫ﻛﺎﺭﻛﻨﺎﻥ ﺩﺍﻧﺸﻲ‬
‫ﻛﺎﺭﻛﺮﺩ‬
‫ﻋﻤﻠﻴﺎﺕ ﺭﻭﺯﺍﻧﻪ‬
‫ﭘﺸﺘﻴﺒﺎﻧﻲ ﺗﺼﻤﻴﻢ‬
‫ﻃﺮﺍﺣﻲ ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ‬
‫ﻛﺎﺭﺑﺮﺩ‪-‬ﮔﺮﺍ‬
‫ﻣﻮﺿﻮﻉ‪-‬ﮔﺮﺍ‬
‫ﺩﺍﺩﻩ‬
‫ﺟﺎﺭﻱ‪ ،‬ﺑﻪﺭﻭﺯ‪ ،‬ﺑﺎﺟﺰﺋﻴﺎﺕ‪،‬‬
‫ﺭﺍﺑﻄﻪﺍﻱ‪،‬ﻣﻨﻔﺮﺩ‬
‫ﺳﺎﺑﻘﻪ‪ ،‬ﺧﻼﺻﻪ ﺷﺪﻩ‪ ،‬ﭼﻨﺪﺑﻌﺪﻱ‪،‬‬
‫ﺳﺮﺟﻤﻊ‪ ،‬ﻳﻜﭙﺎﺭﭼﻪ‬
‫ﻛﺎﺭﺑﺮﺍﻥ‬
‫ﻛﺎﺭﺑﺮﺩ‬
‫ﻋﻤﻠﻴﺎﺕ ﺗﻜﺮﺍﺭﺷﻮﻧﺪﻩ‬
‫ﺧﺎﺹ ﻣﻨﻈﻮﺭﻩ‬
‫‪30‬‬
‫ﻣﻘﺎﻳﺴﻪ ﺟﻨﺒﻪ ﻫﺎﻱ ﻣﺘﻔﺎﻭﺕ ‪) OLAP , OLTP‬ﺍﺩﺍﻣﻪ(‬
‫ﺳﻱﺴﺘﻢ هﺎی‬
‫ﻣﻘﺎ�ﺴﻪ ﺷﺪﻩ‬
‫ﭘﺎﺭﺍﻣ��هﺎی‬
‫ﺍﺭﺯ�ﺎ�ﯽ‬
‫ﭘﺮﺩﺍﺯﺵ ﺗﺮﺍﻛﻥﺶ ﺑﺮﺧﻂ )‪ (OLTP‬ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴ�� ﺑﺮﺧﻂ )‪(OLAP‬‬
‫ﺩﺳ����ﻱ‬
‫ﺧﻮﺍﻧﺪﻥ‪/‬ﻧﻮﺷ�ﻥ‪،‬‬
‫ﺍﻧﺪ�ﺲﮔﺬﺍﺭﻱ‪/‬ﺩﺭهﻢﺳﺎﺯی‬
‫ﺑﺮﺭﻭی �ﻠﻴﺪ ﺍﺻ��‬
‫ﭘﻮﻱﺶ ﺳﺮﺍﺳﺮی ﻭﮔﺴ��ﺩﻩ‬
‫ﻭﺍﺣﺪ �ﺎﺭﻱ‬
‫ﺗﺮﺍﻛﻥﺶهﺎی ﺳﺎﺩﻩ ﻭ �ﻮﺗﺎﻩ‬
‫ﭘﺮﺱﻭﺟﻮهﺎی ﭘﻴﭽﻴﺪﻩ‬
‫�ﻌﺪﺍﺩ ﺭ�ﻮﺭﺩهﺎی ﻣﻮﺭﺩ ﺩﺳ����ﻱ‬
‫ﺩههﺎ ﺭ�ﻮﺭﺩ‬
‫ﻣﻴﻠﻴﻮﻥهﺎ ﺭ�ﻮﺭﺩ‬
‫�ﻌﺪﺍﺩ �ﺎﺭ�ﺮﺍﻥ‬
‫هﺰﺍﺭﺍﻥ �ﺎﺭ�ﺮ‬
‫ﺻﺪهﺎ �ﺎﺭ�ﺮ‬
‫ﺍﻧﺪﺍﺯﻩ ﭘﺎﻳ�ﺎﻩ ﺩﺍﺩﻩ‬
‫ﻣ�ﺎﺑﺎﻳﺖ‪ -‬ﮔﻴ�ﺎﺑﺎﻳﺖ‬
‫ﮔﻴ�ﺎﺑﺎﻳﺖ‪ -‬ﺗﺮﺍﺑﺎﻳﺖ‬
‫‪31‬‬
‫ﻣﻘﺎﻳﺴﻪ ﺟﻨﺒﻪ ﻫﺎﻱ ﻣﺘﻔﺎﻭﺕ ‪) OLAP , OLTP‬ﺍﺩﺍﻣﻪ(‬
‫ﺳﻱﺴﺘﻢ هﺎی‬
‫ﻣﻘﺎ�ﺴﻪ ﺷﺪﻩ‬
‫ﭘﺎﺭﺍﻣ��هﺎی‬
‫ﺍﺭﺯ�ﺎ�ﯽ‬
‫ﻣﻌﻴﺎﺭ ﺳﻨﺠﺶ‬
‫ﭘﺮﺩﺍﺯﺵ ﺗﺮﺍﻛﻥﺶ ﺑﺮﺧﻂ‬
‫)‪(OLTP‬‬
‫ﺑﺎﺯﺩﻩ ﺗﺮﺍﻛﻥﺶ‬
‫)‪(Throughput , Speed‬‬
‫ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴ�� ﺑﺮﺧﻂ‬
‫)‪(OLAP‬‬
‫ﺑﺎﺯﺩﻩ ﭘﺮﺱﻭﺟﻮ‪ ،‬ﭘﺎ�ﺥ‬
‫‪(Throughput,Speed,‬‬
‫) ﺟﺎﻣﻌﻴﺖ ﻭ هﻤﺏﺴﺘ�ﯽ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫‪32‬‬
‫ﻣﺨﺰﻥ ﺩﺍﺩﻩﺍﻱ )‪(Data Warehouse‬‬
‫•‬
‫•‬
‫•‬
‫•‬
‫‪33‬‬
‫‪) Data Warehouse‬ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴﻠﻲ ﻫﻢ ﺑﻪ ﺁﻥ ﮔﻔﺘﻪ ﻣﻲﺷﻮﺩ(‪ ،‬ﻣﺨﺰﻥ ﺩﺍﺩﻩ ﺍﻱ‬
‫ﻣﺘﻤﺮﻛﺰ‪ ،‬ﺟﻤﻊ ﺁﻭﺭﻱ ﺷﺪﻩ ﺍﺯ ﻣﻨﺎﺑﻊ ﺍﻃﻼﻋﺎﺗﻲ ﻣﺨﺘﻠﻒ ﻭ ﻧﺎﻫﻤﮕﻦ ﺩﺭ ﻳﻚ ﻣﺤﺪﻭﺩﻩ ﻭﺳﻴﻊ‬
‫ﺯﻣﺎﻧﻲ ﺍﺳﺖ ﻭ ﺑﺮﺍﻱ ﭘﺸﺘﻴﺒﺎﻧﻲ ﺍﺯ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﺗﺼﻤﻴﻢ ﻳﺎﺭ)‪ (DSS‬ﺍﺳﺘﻔﺎﺩﻩ ﻣﻲ ﺷﻮﺩ‪.‬‬
‫‪ DW‬ﺍﺯ ﭘﺎﻳﮕﺎﻩ ﻫﺎﻱ ﺩﺍﺩﻩ ﻋﻤﻠﻴﺎﺗﻲ ﻭ ﻳﺎ ﺳﺎﻳﺮ ﻣﻨﺎﺑﻊ ﺩﺍﺩﻩ ﺍﻱ ﺗﻮﺯﻳﻊ ﺷﺪﺓ ﺳﺎﺯﻣﺎﻥ ﻫﺎ ﻭ ﺍﺭﮔﺎﻥ‬
‫ﻫﺎﻱ ﻣﺘﻔﺎﻭﺕ ﺗﻬﻴﻪ ﻣﻲ ﺷﻮﺩ‪.‬‬
‫ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﺓ ﺗﺤﻠﻴﻠﻲ ﺑﺴﺘﺮ ﻣﻨﺎﺳﺒﻲ ﻓﺮﺍﻫﻢ ﻣﻲ ﺁﻭﺭﺩ ﻛﻪ ﺩﺍﺩﻩ ﻫﺎ ﺑﻪ ﻣﻨﻈﻮﺭ ﭘﺎﺳﺨﮕﻮﻳﻲ ﺑﻪ‬
‫ﭘﺮﺳﺶ ﻫﺎﻱ ﺗﺤﻠﻴﻠﻲ ﺑﻪ ﺻﻮﺭﺕ ﺑﺎﻳﮕﺎﻧﻲ ﺷﺪﻩ‪ ،‬ﺳﺮ ﺟﻤﻊ ﺷﺪﻩ ﻭ ﺳﺎﺯﻣﺎﻥ ﻳﺎﻓﺘﻪ‪ ،‬ﺫﺧﻴﺮﻩ‬
‫ﺷﻮﻧﺪ‪.‬‬
‫ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴﻠﻲ ﺷﺎﻣﻞ ﺩﺍﺩﻩ ﻫﺎﻳﻲ ﺍﺳﺖ ﻛﻪ ﺑﺮﺍﻱ ﺍﻧﺠﺎﻡ ﺗﺼﻤﻴﻢ ﮔﻴﺮﻱ ﻫﺎ ﻭ ﺗﺤﻠﻴﻞ ﻫﺎ‬
‫ﻣﻨﺎﺳﺐ ﺍﺳﺖ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﻣﺨﺰﻥ ﺩﺍﺩﻩﺍﻱ)ﺍﺩﺍﻣﻪ(‬
‫‪Enterprise‬‬
‫ﺍﻣﻮﺭ ﺍﺩﺍﺭی‬
‫ﻣﺪﻳﺮ�ﺖ‬
‫ﺍﻣﻮﺭ ﻣﺎ��‬
‫ﺗﺤﻠﻴﻠﮕﺮ‬
‫ﭘﺎﻳ�ﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴ��‬
‫ﻳﮑﭙﺎﺭﭼﻪ‬
‫‪Data‬‬
‫‪Marts‬‬
‫ﺍﻣﻮﺭ ﻓﺮﻭﺵ‬
‫ﺍﻣﻮﺭ ﺍﻣﻮﺍﻝ‬
‫ﺍﻣﻮﺭ ﺗﺮﺍﺑﺮی‬
‫‪34‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﺩﺍﺩﻩ ﻛﺎﻭﻱ ) ‪( Data Mining‬‬
‫•‬
‫ﻋﺒﺎﺭﺕ ﺩﺍﺩﻩ ﻛﺎﻭﻱ ﺑﻪ ﻓﺮﺁﻳﻨﺪ ﺗﺤﻠﻴﻞ ﻧﻴﻤﻪ ﺧﻮﺩﻛﺎﺭ ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﻫﺎﻱ ﺑﺰﺭگ‪ ،‬ﺑﻪ ﻣﻨﻈﻮﺭ ﻳﺎﻓﺘﻦ‬
‫ﺍﻟﮕﻮﻫﺎﻱ ﻣﻨﺎﺳﺐ ﺍﻃﻼﻕ ﻣﻲ ﮔﺮﺩﺩ‪.‬‬
‫•‬
‫ﻫﻤﺎﻧﻨﺪ ﻛﺸﻒ ﺩﺍﻧﺶ ﺩﺭ ﻫﻮﺵ ﻣﺼﻨﻮﻋﻲ )ﻛﻪ ﺁﻧﺮﺍ ﻳﺎﺩﮔﻴﺮﻱ ﻣﺎﺷﻴﻦ ﻫﻢ ﻣﻲ ﻧﺎﻣﻨﺪ (‪ ،‬ﻳﺎ‬
‫ﺗﺤﻠﻴﻞ ﺁﻣﺎﺭﻱ‪ ،‬ﺩﺍﺩﻩ ﻛﺎﻭﻱ ﻫﻢ ﺳﻌﻲ ﺩﺭ ﻳﺎﻓﺘﻦ ﻗﻮﺍﻧﻴﻦ ﻭﺍﻟﮕﻮﻫﺎ ﺍﺯ ﺩﺍﺩﻩ ﻫﺎ ﺩﺍﺭﺩ‪.‬‬
‫•‬
‫ﺩﺍﺩﻩ ﻛﺎﻭﻱ ﺍﺯ ﺍﻳﻦ ﺟﻬﺖ ﻛﻪ ﺑﺎ ﺣﺠﻢ ﻋﻈﻴﻢ ﺍﻃﻼﻋﺎﺗﻲ‪ ،‬ﻛﻪ ﺍﻏﻠﺐ ﺭﻭﻱ ﺩﻳﺴﻚ ﺫﺧﻴﺮﻩ ﺷﺪﻩ‬
‫ﺍﺳﺖ ﺭﻭﺑﺮﻭﺳﺖ‪ ،‬ﺑﺎ ﻳﺎﺩﮔﻴﺮﻱ ﻣﺎﺷﻴﻦ ﻭ ﺁﻣﺎﺭ ﻣﺘﻔﺎﻭﺕ ﺍﺳﺖ‪.‬‬
‫•‬
‫‪35‬‬
‫ﺩﺍﺩﻩ ﻛﺎﻭﻱ ﺑﺎ ﻛﺸﻒ ﺩﺍﻧﺶ ﺩﺭ ﭘﺎﻳﮕﺎﻩ ﻫﺎﻱ ﺩﺍﺩﻩ ﺳﺮ ﻭ ﻛﺎﺭ ﺩﺍﺭﺩ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﻣﻌﻤﺎﺭی ﭼﻨﺪ ﻻﻳﻪ‬
‫�ﺎﺭ�ﺮﺩهﺎ‬
‫‪Monitor‬‬
‫&‬
‫‪Integrator‬‬
‫ﺗﺤﻠﻴﻞ‬
‫ﺩﺍﺩﻩ�ﺎﻭی‬
‫ﭘﺮﺱﻭﺟﻮ ﻭ‬
‫ﮔﺰﺍﺭﺵﮔ��ﻱ‬
‫ﺳﺮﻭﻱﺲ‬
‫ﭘﺎﻳ�ﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴ��‬
‫ﺩﺍﺩﻩﺟﺎﻧ�ﻱ‬
‫ﺍﺳﺘﺨﺮﺍﺝ‬
‫�ﻐﻴ��ﺷ�ﻞ‬
‫ﺑﺎﺭﮔﺬﺍﺭﻱ‬
‫ﻧﻮﺳﺎﺯﻱ‬
‫ﺳﺎﻳﺮﻣﻨﺎ�ﻊ‬
‫ﭘﺎﻳ�ﺎﻩهﺎی ﺩﺍﺩﻩ‬
‫‪Data Marts‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫هﺎی ﺳﻄﺢ ﺑﺎﻻ‬
‫‪ 36‬ﺍﺑﺰﺍﺭ‬
‫ﻓﺮﻓﺎ‬
‫‪OLAP‬‬
‫ﭘﺎﻳ�ﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴ��‬
‫ﻣﻨﺎ�ﻊ ﺩﺍﺩﻩ‬
‫ﻣﺤﻴﻂ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫ﺩﺍﺩﻩ �ﺎﻭی‬
‫‪‬ﺗﻘﺳﻳﻡ ﺑﻧﺩی ﻣﺷﺗﺭی‬
‫ﭘﺎﯾ�ﺎﻩ ﺍﻃﻼﻋﺎﺕ‬
‫ﭘﺎﻳ�ﺎﻩ ﺩﺍﺩﻩ‬
‫‪‬ﺗﺷﺧﻳﺹ ﺗﻘﻠﺏ‬
‫ﺗﺤﻠﻴ��‬
‫ﺗﺤﻠﻴ��‬
‫‪‬ﺑﺎﺯﺍﺭ ﻣﻘﺻﺩ‬
‫ﺗﺠﺎﺭی‬
‫ﺗﺠﺎﺭی‬
‫‪...‬‬
‫ﭘﺭﺱ ﻭﺟﻭ‪OLAP /‬‬
‫‪‬ﭘﺭﺱ ﻭ ﺟﻭﻫﺎی ﺗﺟﺎﺭی‬
‫‪‬ﺁﻧﺎﻟﻳﺯ ﭼﻧﺩﺑﻌﺩی‬
‫‪...‬‬
‫‪3‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ ﻓﺮﻓﺎ‬
‫‪7‬‬
‫ﺍﺳﺘﺨﺮﺍﺝ ‪ /‬ﺗﮑﺮﺍﺭ‬
‫ﭘﺎﮐﺴﺎﺯی ﺩﺍﺩﻩ‬
‫ﻣﺪﻳﺮ�ﺖ ﻓﺮﺍ ﺩﺍﺩﻩ‬
‫ﺩﺍﺩﻩ‬
‫ﻋﻤﻠﻴﺎ�ﯽ‬
‫ﺳﺎﻣﺎﻧﻪﻫﺎﻱ ﻫﻮﺷﻤﻨﺪ ﺗﺼﻤﻴﻢﻳﺎﺭ‬
‫‪38‬‬
‫•‬
‫ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﺗﺼﻤﻴﻢ ﻳﺎﺭ‪ ،‬ﺳﻴﺴﺘﻢ ﻫﺎﻳﻲ ﻫﺴﺘﻨﺪ ﻛﻪ ﺑﻪ ﻣﺪﻳﺮﺍﻥ ﺩﺭﺍﻣﺮ ﺗﺼﻤﻴﻢ ﮔﻴﺮ ﻱ ﻛﻤﻚ‬
‫ﻣﻲ ﻛﻨﻨﺪ‪.‬‬
‫•‬
‫ﺑﺮﺍﻱ ﺍﻳﻦ ﻣﻨﻈﻮﺭ ﺍﺯ ﺗﻜﻨﻴﻚ ﻫﺎﻳﻲ ﻣﺎﻧﻨﺪ ﺩﺍﺩﻩ ﻛﺎﻭﻱ ﻭ ﺳﺮﻭﻳﺲ ﻫﺎﻳﻲ ﻣﺎﻧﻨﺪ ‪ OLAP‬ﻛﻤﻚ‬
‫ﻣﻲ ﮔﻴﺮﻧﺪ‪.‬‬
‫•‬
‫ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴﻠﻲ )‪ (DW‬ﻭ ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮ ﺧﻂ )‪ (OLAP‬ﺍﺯ ﺟﻤﻠﻪ ﻋﻨﺎﺻﺮ ﺿﺮﻭﺭﻱ‬
‫ﺩﺭ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﺗﺼﻤﻴﻢ ﻳﺎﺭ ﺑﻪ ﺷﻤﺎﺭ ﻣﻲ ﺁﻳﻨﺪ‪.‬‬
‫•‬
‫ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﺗﺼﻤﻴﻢ ﻳﺎﺭ ﻫﻮﺷﻤﻨﺪ‪ ،‬ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﺗﺼﻤﻴﻢ ﻳﺎﺭﻱ ﻫﺴﺘﻨﺪ ﻛﻪ ﻣﺒﺘﻨﻲ ﺑﺮ‬
‫ﺗﻜﻨﻴﻚ ﻫﺎﻱ ﻫﻮﺷﻤﻨﺪ ﺍﻧﺪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﻋﺎﻣﻞ هﻮﺷﻤﻨﺪ‬
‫•‬
‫ﻋﺎﻣﻞ )‪ (Agent‬ﻧﺮﻡ ﺍﻓﺰﺍﺭﻱ ﺍﺳﺖ ﻛﻪ ﻗﺎﺩﺭ ﺑﻪ ﺗﺄﺛﻴﺮ ﮔﺬﺍﺭﻱ ﺑﺮ ﻣﺤﻴﻂ ﺍﺳﺖ ﺑﻪ ﻃﻮﺭﻱ ﻛﻪ‬
‫ﻣﻨﺠﺮ ﺑﻪ ﻓﻌﺎﻟﻴﺖ ﻭ ﻳﺎ ﺗﻐﻴﻴﺮﺣﺎﻟﺖ ﻣﻲ ﺷﻮﺩ‪ .‬ﻫﻤﺎﻧﻨﺪ ﻳﻚ ﻓﻌﺎﻟﻴﺖ ﺷﻴﻤﻴﺎﻳﻲ‪ ،‬ﻓﻴﺰﻳﻜﻲ ﻭ ﻳﺎ‬
‫ﺑﻴﻮﻟﻮژﻳﻜﻲ ‪.‬‬
‫•‬
‫•‬
‫•‬
‫ﻋﺎﻣﻞ ﺍﺑﺰﺍﺭﻱ ﻫﻮﺷﻤﻨﺪ ﺑﺮﺍﻱ ﺭﺳﻴﺪﻥ ﺑﻪ ﻫﺪﻑ ﺍﺳﺖ ‪.‬‬
‫•‬
‫‪39‬‬
‫ﻋﺎﻣﻞ ﺧﻮﺩﻣﺨﺘﺎﺭ ﺍﺳﺖ ﻭ ﺑﻪ ﺗﻨﻬﺎﻳﻲ ﻗﺎﺩﺭ ﺑﻪ ﺗﺼﻤﻴﻢ ﮔﻴﺮﻱ ﺍﺳﺖ‪.‬‬
‫ﻋﺎﻣﻞ ﻋﺒﺎﺭﺕ ﺍﺳﺖ ﺍﺯ ﻣﻮﺟﻮﺩﻳﺘﻲ ﻛﻪ ﻭﺍﻛﻨﺶ ﺩﺍﺭﺩ ﻭ ﺑﻪ ﻃﻮﺭ ﺧﻮﺩﻣﺨﺘﺎﺭ ﻛﻨﺶ ﺍﻧﺠﺎﻡ ﻣﻲ‬
‫ﺩﻫﺪ‪.‬‬
‫ﻋﺎﻣﻠﻬﺎﻱ ﻫﻮﺷﻤﻨﺪ ﺑﺎﻳﺴﺘﻲ ﻗﺎﺩﺭ ﺑﻪ ﺍﻧﺠﺎﻡ ﻛﺎﺭﻫﺎ ﺩﺭ ﺩﻧﻴﺎﻱ ﻭﺍﻗﻌﻲ ﺑﺎﺷﻨﺪ ﺑﻪ ﻃﻮﺭﻱ ﻛﻪ‬
‫ﺍﻋﻤﺎﻝ ﻫﺪﻓﺪﺍﺭﻱ ﺭﺍ ﺍﻧﺠﺎﻡ ﺩﻫﻨﺪ ﻭ ﻧﻴﺰ ﺑﺎﻳﺴﺘﻲ ﻗﺎﺩﺭ ﺑﻪ ﺯﻧﺪﮔﻲ ﻭ ﻋﻤﻞ ﺩﺭ ﺩﻧﻴﺎﻱ ﻭﺍﻗﻌﻲ‬
‫ﺑﺎﺷﻨﺪ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﻭ�ﮋ�ﯽ هﺎی ﻋﺎﻣﻞ هﺎ‬
‫ﻭ�ﮋ�ﯽ‬
‫ﭘﺮﺩﺍﺧ�ﻥ ﺑﻪ ﻋﻤﻞ ﺑﺎ ﺗﻮﺟﻪ ﺑﻪ هﺪﻑ �ﻌﺮ�ﻒ ﺷﺪﻩ ﺑﺪﻭﻥ ﻓﺮﺍﺧﻮﺍ �ﻲ‬
‫ﺧﻮﺩ ﻣﺨﺘﺎﺭﻱ‬
‫‪Autonomy‬‬
‫ﻣﻮﻗﻴﻌﺖ ﮔﺮﺍ‬
‫‪ Situatedness‬ﻭﺍ�ﺴﺘﻪ ﺑﻪ ﻣﺤﻴﻂ ﻭ ﺷﺮﺍﻳﻂ ﻋﻤﻠﻴﺎ�ﻲ‬
‫ﺩﺭﻙ ﻣﺤﻴﻂ ﻭ ﭘﺎ�ﺥ ﺑﻪ �ﻐﻴ��ﺍﺕ ﺁﻥ‬
‫‪Reactive‬‬
‫ﻭﺍﻛﻥ��ی‬
‫‪40‬‬
‫ﻭﺍژﻩ ﻻﺗ�ﻥ‬
‫ﺗﻮﺻﻴﻒ ﻣﺨﺘﺼﺮ ﻭ�ﮋ�ﯽ‬
‫ﻛﻥﺶ ﮔﺮﺍ‬
‫‪Pro-active‬‬
‫ﻧﻤﺎ�ﺶ ﺭﻓﺘﺎﺭهﺎی هﺪﻓﻤﻨﺪ �ﻌﺮ�ﻒ ﺷﺪﻩ‬
‫ﻳﺎﺩﮔ��ی‬
‫‪Learning‬‬
‫�ﻐﻴ�� ﺭﻓﺘﺎﺭهﺎ ﺑﺮ ﺍﺳﺎﺱ ﺗﮑﺮﺍﺭ ﺭﻓﺘﺎﺭ‬
‫ﺻﺪﺍﻗﺖ‬
‫‪Veracity‬‬
‫ﻋﺪﻡ ﺍﻧﺘﻘﺎﻝ ﺍﻃﻼﻋﺎﺕ ﻧﺎﺩﺭﺳﺖ‬
‫ﭘﺎﻳﺪﺍﺭی‬
‫‪Persistency‬‬
‫ﺩﺍﺭﺍی ﺍهﺪﺍﻑ ﻭ ﻓﺮﺁﻳﻨﺪهﺎی ﺫﺍ�ﯽ ﺍﺯ ﭘﻱﺶ �ﻌﺮ�ﻒ ﺷﺪﻩ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻭ�ﮋ�ﯽ هﺎی ﻋﺎﻣﻞ هﺎ )ﺍﺩﺍﻣﻪ(‬
‫‪41‬‬
‫ﺍﺟﺘﻤﺎ��‬
‫‪Social‬‬
‫هﻤ�ﺎﺭی ﺑﺎ ﺳﺎﻳﺮ ﻋﺎﻣﻞ هﺎ ﺩﺭ ﺳﻱﺴﺘﻤهﺎی ﭼﻨﺪ ﻋﺎﻣﻠﻪ‬
‫هﺪﻑ ﮔﺮﺍ‬
‫‪Goal-oriented‬‬
‫ﺗﺤﻘﻖ هﺪﻑ ﺳﻱﺴﺘﻢ ﺗﺎ ﺩﺳﺕﻴﺎ�ﯽ ﺑﻪ ﺁﻥ ﺑﺪﻭﻥ ﻓﺮﺍﺧﻮﺍ�ﻲ‬
‫ﺍﺳﺘﺪﻻﻝ‬
‫‪Reasoning‬‬
‫ﻗﺎﺑﻠﻴﺖ ﺍﺳﺘﺪﻻﻝ ﺩﺭ ﺍﻧﺘﺨﺎﺏ ﻋﻤﻞ‬
‫ﺳﺎﺯ�ﺎﺭی‬
‫‪Adaptivity‬‬
‫ﺍﻣ�ﺎﻥ ﺗﻄﺎﺑﻖ ﺍﻋﻤﺎﻝ ﻳﻚ ﻋﺎﻣﻞ ﺑﺎ ﺍهﺪﺍﻑ ﻛ�� ﺳﻱﺴﺘﻢ‬
‫ﺣﺮﻛﺖ‬
‫‪Mobility‬‬
‫ﻗﺎﺑﻠﻴﺖ ﺍﻧﺘﻘﺎﻝ ﺍﺯ ﻣﺤﻴﻄﯽ ﺑﻪ ﻣﺤﻴﻄﯽ ﺩﻳﮕﺮ‬
‫ﻧﻮﻉ ﺩﻭﺳ�ﻱ‬
‫‪Benevolance‬‬
‫ﻣﺼﺎ�ﺡﻪ ﺩﺭ ﻣﻨﺎﻓﻊ ﻣﺮﺗﺒﻂ ﺑﺎ ﻋﺎﻣﻠهﺎی هﻤ�ﺎﺭ‬
‫ﻧﻤﺎﻳﻨﺪ�ﻲ‬
‫‪Delegacy‬‬
‫ﻗﺒﻮﻝ ﺍﻧﺠﺎﻡ ﻋﻤﻞ ﺩﺭ ﺳﻱﺴﺘﻤهﺎی ﭼﻨﺪ ﻋﺎﻣﻠﻪ‬
‫ﺷﺎ�ﺴﺘ�ﻲ‬
‫‪Competency‬‬
‫ﺍﺭﺯ�ﺎ�ﯽ ﻓﻌﺎﻟﻴﺖ ﺍﻧﺠﺎﻡ ﺷﺪﻩ ﺩﺭ ﺗﺤﻘﻖ هﺪﻑ ﻭ ﺗﻘﺴﻴﻢ ﻭﻇﺎﻳﻒ ﺩﺭ‬
‫ﺻﻮﺭﺕ ﻟﺰﻭﻡ‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻭ�ﮋ�ﯽ هﺎی ﻋﺎﻣﻞ هﺎ )ﺍﺩﺍﻣﻪ(‬
‫ﺍﺣﺴﺎﺱ ﻣﺴﺌﻮﻟﻴﺖ‬
‫ﻗﺪﺭﺕ ﺍﺳﺘﺪﻻﻝ‬
‫‪Discourse‬‬
‫ﻗﺎﺑﻠﻴﺖ ﺍﺳﺘﺪﻻﻝ ﺩﺭ ﺍﻧﺘﺨﺎﺏ ﻋﻤﻞ ﻭﺍ�ﺴﺘﻪ ﺑﻪ ﻣﺤﻴﻂ‬
‫ﻋﻘﻼﻧﻱﺖ‬
‫‪Rationality‬‬
‫ﺍﻋﻤﺎﻝ ﺩﺭﺳﺖ ﺑﺮﺍی ﺭﺳﻴﺪﻥ ﺑﻪ ﺍهﺪﺍﻑ‬
‫ﺳﻱﺴﺘﻢ‬
‫ﻣﺤﻴﻂ‬
‫‪S‬‬
‫‪E‬‬
‫‪N‬‬
‫‪S‬‬
‫‪O‬‬
‫‪R‬‬
‫ﻭﺭﻭﺩی‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫‪E‬‬
‫‪F‬‬
‫‪F‬‬
‫‪E‬‬
‫‪C‬‬
‫‪T‬‬
‫‪O‬‬
‫‪R‬‬
‫ﺧﺮﻭ��‬
‫‪42‬‬
‫‪ Amenability‬ﺍﺭﺯ�ﺎ�ﯽ ﺗﺤﻘﻖ هﺪﻑ ﺳﻱﺴﺘﻢ ﻭ ﺍﺩﺍﻣﻪ ﻋﻤﻞ ﺗﺎ ﺗﺤﻘﻖ هﺪﻑ‬
‫ﻧﻤﺎ���ی ﺍﺯ ﻋﺎﻣﻞ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫)‪ERP (Enterprise Resource Planing‬‬
‫‪43‬‬
‫•‬
‫ﻣﺠﻤﻮﻋﻪ ﺍﻱ ﺍﺯ ﻧﺮﻡ ﺍﻓﺰﺍﺭﻫﺎﻱ ﻛﺎﺭﺑﺮﺩﻱ ﻣﻮﺭﺩ ﺍﺳﺘﻔﺎﺩﻩ ﺩﺭ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﻋﻤﻠﻴﺎﺗﻲ‬
‫ﻣﺠﺘﻤﻊ‪ ،‬ﺑﻪ ﻣﻨﻈﻮﺭ ﭘﺸﺘﻴﺒﺎﻧﻲ ﺍﺯ ﭘﺮﺩﺍﺯﺵ ﻫﺎﻱ ﺗﺠﺎﺭﻱ ﻋﻤﻠﻴﺎﺗﻲ ﻣﺒﺘﻨﻲ ﺑﺮ ﻣﻌﻤﺎﺭﻱ‬
‫‪.Enterprise‬‬
‫•‬
‫ﻳﻚ ‪ ERP‬ﻳﻚ ﺳﺎﻣﺎﻧﻪ ﻣﺒﺘﻨﻲ ﺑﺮ ﻛﺎﻣﭙﻴﻮﺗﺮ ﺍﺳﺖ ﻛﻪ ﺗﻤﺎﻡ ﺷﻌﺒﺎﺕ ﻭ ﻭﻇﺎﻳﻒ ﻳﻚ‬
‫ﺳﺎﺯﻣﺎﻥ ﺭﺍ ﻳﻜﭙﺎﺭﭼﻪ ﻣﻲ ﻛﻨﺪ‬
‫•‬
‫ﻳﻚ ‪ ERP‬ﻫﻤﻪ ﻓﺮﺁﻳﻨﺪﻫﺎﻱ ﺗﺠﺎﺭﻱ ﻣﻬﻢ ﺭﺍ ﺑﺎ ﻳﻚ ﻣﻌﻤﺎﺭﻱ ﻭﺍﺣﺪ ﺑﺼﻮﺭﺕ ﻟﺤﻈﻪ ﺑﻪ‬
‫ﻟﺤﻈﻪ ﻛﻨﺘﺮﻝ ﻣﻲ ﻛﻨﺪ‪.‬‬
‫•‬
‫ﺍﻧﺘﻈﺎﺭ ﻣﻲ ﺭﻭﺩ ﺭﺍﻩ ﺣﻞ ﻳﻜﭙﺎﺭﭼﻪ ﺍﺯ ﻛﺎﺭﺍﻳﻲ ﺗﺎ ﻛﻴﻔﻴﺖ‪ ،‬ﺑﻬﺮﻩ ﻭﺭﻱ ﻭ ﺳﻮﺩ ﺭﺍ ﺑﻬﺒﻮﺩ ﺑﺨﺸﺪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫‪Enterprise Information Management‬‬
‫ﻓﺮﻭﺵ‬
‫ﻟﻱﺴﺖ ﺍﻣﻮﺍﻝ‬
‫ﺗﻮﺯﻱﻊ‬
‫�ﺸﺘﻱﺒﺎ�ﯽ ﻣﺸ��ی‬
‫‪IT‬‬
‫ﻗﻴﻤﺖ ﮔﺬﺍﺭی ﻣﺤﺼﻮﻝ‬
‫‪IT‬‬
‫‪IT‬‬
‫ﺍﻣﻮﺭ ﻣﺎ��‬
‫‪Clien t‬‬
‫‪Client‬‬
‫‪Client‬‬
‫‪Client‬‬
‫‪Client‬‬
‫‪Client‬‬
‫ﺑﺎﺯﺍﺭ‬
‫ﻭﺍﺣﺪ ﺗﺠﺎﺭی‬
‫‪Clien‬‬
‫‪IT‬‬
‫‪IT‬‬
‫‪IT‬‬
‫‪IT‬‬
‫ﻭﺍﺣﺪ ﺗﮑﻨﻮﻟﻮژی ﺍﻃﻼﻋﺎﺕ‬
‫ﻣﺪﻳﺮ�ﺖ ﺍﻃﻼﻋﺎﺕ‬
‫‪Enterprise‬‬
‫ﻣﺤﻴﻂ �ﺸﺘﻱﺒﺎ�ﯽ‬
‫ﺍﺯ ﺗﺼﻤﻴﻢ ﮔ��ی‬
‫‪44‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﮐﻨ��ﻝ ‪ ,‬ﻣﺴﺕﻨﺪﺍﺕ ‪ ,‬ﺟﻤﻊ ﺁﻭﺭی ‪ ,‬هﻤﺎهﻨ�ﯽ ‪ ,‬ﮐﺸﻒ ﮐﺮﺩﻥ‬
‫‪OM‬‬
‫‪DM‬‬
‫‪ODS‬‬
‫‪EDW‬‬
‫‪BI/DW Databases‬‬
‫‪Operational Systems‬‬
‫ﻣﺤﻴﻂ ﻋﻤﻠﻴﺎ�ﯽ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﻧﻘﺸﻪ ﺭﺍﻩ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫‪45‬‬
‫•‬
‫ﺑﺮﺍﻱ ﺑﺮﻧﺎﻣﻪ ﻫﺎﻱ ﻛﺎﺭﺑﺮﺩﻱ ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺑﺎ ﻧﻴﺎﺯﻣﻨﺪﻱ ﻫﺎﻱ ﺧﺎﺹ ﺍﺯ ﺟﻤﻠﻪ ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﺩﺍﺩﻩ‬
‫ﻫﺎﻱ ﻏﻴﺮ ﺳﺎﺧﺖ ﻳﺎﻓﺘﻪ ﻣﺜﻼً ﻛﺎﻭﺵ ﺩﺭ ﻣﺘﻦ ﻭ ﻣﺤﺘﻮﺍ ﻭ ﺻﻮﺕ ﻭ‪ ...‬ﻧﻴﺎﺯ ﺑﻪ ﮔﺴﺘﺮﺵ ﻓﻌﺎﻟﻴﺖ‬
‫ﻫﺎ ﻭ ﻧﻘﺶ ﻫﺎ ﺩﺭ ﻗﺎﻟﺐ ﮔﺎﻡ ﻫﺎﻱ ﺗﻮﻟﻴﺪ ﻣﻨﺎﺳﺐ ﺍﺳﺖ‬
‫•‬
‫ﻧﻘﺸﻪ ﺭﺍﻩ ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺍﺳﺎﺳﺎً ﻳﻚ ﺭﺍﻫﻨﻤﺎﻱ ﭼﺮﺧﺔ ﺣﻴﺎﺕ ﭘﺮﻭژﻩ ﺑﺮﺍﻱ ﺍﻳﺠﺎﺩ ﺑﺮﻧﺎﻣﻪ ﻫﺎﻱ‬
‫ﻛﺎﺭﺑﺮﺩﻱ ﺗﺼﻤﻴﻢ ﻳﺎﺭﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺑﺎ ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﺩﺍﺩﻩ ﻫﺎﻱ ﺳﺎﺧﺖ ﻳﺎﻓﺘﻪ ﺍﺳﺖ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﻧﻘﺸﺔ ﺭﺍﻩ ﺗﻮﻟﻴﺪ ﻳﮏ ﭘﺮﻭژﺓ هﻮﺵ ﺗﺠﺎﺭی)‪(1‬‬
‫•‬
‫ﺍﻳﻦ ﻧﻘﺸﻪ ‪ 16‬ﮔﺎﻡ ﺑﺮﺍﻱ ﺳﺎﺧﺖ ﻳﻚ ﭘﺮﻭژﺓ ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺭﺍ ﺑﺮ ﻃﺒﻖ ﻫﻤﺎﻥ ‪ 6‬ﻣﺮﺣﻠﺔ ﺍﻧﺠﺎﻡ ﻫﺮ ﭘﺮﻭژﺓ‬
‫ﻣﻬﻨﺪﺳﻲ ﺑﻪ ﺷﺮﺡ ﺯﻳﺮ ﺑﻴﺎﻥ ﻣﻲ ﻛﻨﺪ‪:‬‬
‫• ﻣﺮﺣﻠﺔ ﻫﺪﻑ ﻭ ﻣﻨﻈﻮﺭ‪:‬‬
‫• ﮔﺎﻡ ‪ :1‬ﺍﺭﺯﻳﺎﺑﻲ ﻭﺿﻌﻴﺖ ﺗﺠﺎﺭﻱ‪،‬‬
‫• ﻣﺮﺣﻠﺔ ﻃﺮﺡ ﺭﻳﺰﻱ‪:‬‬
‫•‬
‫‪46‬‬
‫•‬
‫•‬
‫ﮔﺎﻡ ‪ :2‬ﺍﺭﺯﻳﺎﺑﻲ ﺯﻳﺮ ﺳﺎﺧﺖ ‪،Enterprise‬‬
‫ﮔﺎﻡ ‪ :3‬ﻃﺮﺡ ﺭﻳﺰﻱ ﭘﺮﻭژﻩ‪،‬‬
‫•‬
‫•‬
‫•‬
‫•‬
‫ﮔﺎﻡ ‪ :4‬ﺗﻌﺮﻳﻒ ﻧﻴﺎﺯﻣﻨﺪﻱ ﻫﺎﻱ ﭘﺮﻭژﻩ‪،‬‬
‫ﮔﺎﻡ ‪ :5‬ﺗﺤﻠﻴﻞ ﺩﺍﺩﻩ‪،‬‬
‫ﮔﺎﻡ ‪ :6‬ﻧﻤﻮﻧﻪ ﺳﺎﺯﻱ ﺑﺮﻧﺎﻣﻪ ﻛﺎﺭﺑﺮﺩﻱ‪،‬‬
‫ﮔﺎﻡ ‪ :7‬ﺗﺤﻠﻴﻞ ﻣﺨﺰﻥ ﻓﺮﺍﺩﺍﺩﻩ‪،‬‬
‫ﻣﺮﺣﻠﺔ ﺗﺤﻠﻴﻞ ﺗﺠﺎﺭﻱ‪:‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﻧﻘﺸﺔ ﺭﺍﻩ ﺗﻮﻟﻴﺪ ﻳﻚ ﭘﺮﻭژﺓ ﻫﻮﺵ ﺗﺠﺎﺭﻱ)‪(1‬‬
‫•‬
‫•‬
‫•‬
‫‪47‬‬
‫ﻣﺮﺣﻠﺔ ﻃﺮﺍﺣﻲ‪:‬‬
‫• ﮔﺎﻡ ‪ :8‬ﻃﺮﺍﺣﻲ ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ‪،‬‬
‫• ﮔﺎﻡ ‪ :9‬ﻃﺮﺍﺣﻲ ‪) ETL‬ﺍﺳﺘﺨﺮﺍﺝ‪/‬ﺗﺒﺪﻳﻞ‪/‬ﺑﺎﺭﮔﺬﺍﺭﻱ(‬
‫• ﮔﺎﻡ ‪ :10‬ﻃﺮﺍﺣﻲ ﻣﺨﺰﻥ ﻓﺮﺍﺩﺍﺩﻩ‪،‬‬
‫ﻣﺮﺣﻠﺔ ﺳﺎﺧﺖ‪:‬‬
‫• ﮔﺎﻡ ‪ :11‬ﺗﻮﻟﻴﺪ ‪،ETL‬‬
‫• ﮔﺎﻡ ‪ :12‬ﺗﻮﻟﻴﺪ ﺑﺮﻧﺎﻣﺔ ﻛﺎﺭﺑﺮﺩﻱ‪،‬‬
‫• ﮔﺎﻡ ‪ :13‬ﺩﺍﺩﻩ ﻛﺎﻭﻱ‪،‬‬
‫• ﮔﺎﻡ ‪ :14‬ﺗﻮﻟﻴﺪ ﻣﺨﺰﻥ ﻓﺮﺍﺩﺍﺩﻩ‪،‬‬
‫ﻣﺮﺣﻠﺔ ﻧﺼﺐ ﻭ ﺍﺳﺘﻘﺮﺍﺭ‪:‬‬
‫• ﮔﺎﻡ ‪ :15‬ﭘﻴﺎﺩﻩ ﺳﺎﺯﻱ‪،‬‬
‫• ﮔﺎﻡ ‪ :16‬ﺍﺭﺯﻳﺎﺑﻲ ﻧﺴﺨﻪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺍﺭﺯﻳﺎﺑﻲ ﻭﺿﻌﻴﺖ ﺗﺠﺎﺭﻱ‬
‫•‬
‫‪48‬‬
‫ﺩﺭ ﺍﻳﻦ ﮔﺎﻡ‪ ،‬ﻣﺸﻜﻞ ﻳﺎ ﻣﻮﻗﻌﻴﺖ ﺗﺠﺎﺭﻱ ﺗﻌﺮﻳﻒ ﻣﻲ ﺷﻮﺩ ﻭ ﻳﻚ ﺭﺍﻩ ﺣﻞ ﺗﺠﺎﺭﻱ ﭘﻴﺸﻨﻬﺎﺩ ﻣﻲ ﺷﻮﺩ‪.‬‬
‫ﻫﺮ ﻧﺴﺨﺔ ﺑﺮﻧﺎﻣﺔ ﻛﺎﺭﺑﺮﺩﻱ ﻫﻮﺵ ﺗﺠﺎﺭﻱ ﺑﺎﻳﺪ ﺗﻮﺟﻴﻪ ﺍﻗﺘﺼﺎﺩﻱ ﺩﺍﺷﺘﻪ ﺑﺎﺷﺪ ﻭ ﺑﻪ ﻃﻮﺭ ﻭﺍﺿﺢ ﺑﺎﻳﺪ‬
‫ﻓﻮﺍﻳﺪ ﺁﻥ ﺭﺍﻩ ﺣﻞ ﺑﻴﺎﻥ ﺷﻮﺩ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﺷﻤﺎی ﻧﻘﺸﺔ ﺭﺍﻩ ﺗﻮﻟﻴﺪ ﻳﮏ ﭘﺮﻭژﺓ هﻮﺵ ﺗﺠﺎﺭی‬
‫�ﺎﻡ ‪11‬‬
‫�ﺎﻡ ‪16‬‬
‫�ﺎﻡ ‪15‬‬
‫ﺍﺳﺘﻘﺮﺍﺭ‬
‫�ﺎﻡ ‪12‬‬
‫�ﺎﻡ ‪8‬‬
‫�ﺎﻡ ‪6‬‬
‫�ﺎﻡ ‪13‬‬
‫�ﺎﻡ ‪14‬‬
‫ﺳﺎﺧﺖ‬
‫‪49‬‬
‫�ﺎﻡ ‪9‬‬
‫�ﺎﻡ ‪5‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫�ﺎﻡ ‪10‬‬
‫ﻃﺮﺍ��‬
‫�ﺎﻡ ‪4‬‬
‫�ﺎﻡ ‪7‬‬
‫�ﺎﻡ ‪3‬‬
‫�ﺎﻡ ‪2‬‬
‫ﻃﺮﺡ ﺭ�ﺰی‬
‫ﺗﺤﻠﻴﻞ ﺗﺠﺎﺭی‬
‫ﻓهﺮﺳﺖ‬
‫�ﺎﻡ ‪1‬‬
‫هﺪﻑ‬
‫ﺍﺟﺮﺍی ﻣﻮﺍﺯی ﻧﻘﺸﺔ ﺭﺍﻩ ﺳﺎﺧﺖ ﻳﮏ ﭘﺮﻭژﺓ ‪BI‬‬
‫ﺍﺟﺮﺍی ﻣﻮﺍﺯی �ﺎﻡ هﺎ‬
‫‪11‬‬
‫‪16‬‬
‫‪50‬‬
‫ﺯﻣﺎﻥ‬
‫‪13 14‬‬
‫‪9‬‬
‫‪10‬‬
‫‪12‬‬
‫‪8‬‬
‫‪7‬‬
‫‪6‬‬
‫‪4 5‬‬
‫‪15‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫‪3‬‬
‫‪2‬‬
‫‪1‬‬
‫ﻣﻼﺣﻈﺎﺕ ﻧﻘﺸﻪ ﺭﺍﻩ ﺳﻴﺴﺘﻢ ﻫﺎﻱ ﻫﻮﺵ ﺗﺠﺎﺭﻱ )‪(2‬‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫•‬
‫‪51‬‬
‫ﺷﻨﺎﺧﺖ ﻛﻴﻔﻴﺖ ﺩﺍﺩﻩ‪،‬‬
‫ﺷﻨﺎﺧﺖ ﻋﺪﻡ ﻛﻴﻔﻴﺖ ﺩﺍﺩﻩ‪،‬‬
‫ﺗﺼﺤﻴﺢ ﺩﺍﺩﻩ ﻫﺎ‪،‬‬
‫ﺍﺷﺘﺮﺍﻙ ﮔﺬﺍﺭﻱ ﺩﺍﺩﻩ ﻫﺎ‪،‬‬
‫ﺩﺍﺩﻩ ﺑﻪ ﻣﻨﺰﻟﻪ ﺳﺮﻣﺎﻳﻪ ﺗﻠﻘﻲ ﺷﻮﺩ‪،‬‬
‫ﺗﻮﻟﻴﺪ ﺩﺍﺩﻩ ﺍﺯ ﺩﺍﺩﻩ ﻫﺎﻱ ﻣﻮﺟﻮﺩ )ﻳﺎﺩﮔﻴﺮﻱ‪ +‬ﺍﺳﺘﻨﺘﺎﺝ(‪،‬‬
‫ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﺍﺳﺘﺎﻧﺪﺍﺭﺩﻫﺎ‪،‬‬
‫ﻛﻮﭼﻚ ﻭﻣﺤﺪﻭﺩﻧﻤﻮﺩﻥ ﻣﺤﺪﻭﺩﺓ ﺳﻴﺴﺘﻢ ﻫﺎ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺳﺎﺧﺘﺎﺭ ﺗﻴﻢ ﭘﺮﻭژﻩ‬
‫•‬
‫•‬
‫•‬
‫•‬
‫‪52‬‬
‫ﻋﻤﻮﺩﻱ ﻳﺎ ﺍﻓﻘﻲ‬
‫ﻣﺘﻤﺮﻛﺰ ﻳﺎ ﻏﻴﺮﻣﺘﻤﺮﻛﺰ‪ :‬ﻛﻪ ﺩﺭﺑﺮﻧﺎﻣﻪ ﻫﺎﻱ ﻣﺒﺘﻨﻲ ﺑﺮ ﻣﺆﻟﻔﻪ ﺍﺯ ﺳﺎﺧﺘﺎﺭ ﻣﺘﻤﺮﻛﺰ ﺍﺳﺘﻔﺎﺩﻩ ﻣﻲ ﺷﻮﺩ‬
‫ﻋﻤﻮﺩﻱ ﻣﺘﻤﺮﻛﺰ ﻳﺎ ﺍﻓﻘﻲ ﻏﻴﺮ ﻣﺘﻤﺮﻛﺰ‬
‫ﺑﺮﺍﻱ ﻳﻚ ﺳﻴﺴﺘﻢ ‪ BI‬ﭘﻴﺸﻨﻬﺎﺩ ﻣﻲ ﺷﻮﺩ ﺍﺯ ﻳﻚ ﺳﺎﺧﺘﺎﺭ ﻏﻴﺮ ﻣﺘﻤﺮﻛﺰ ﺍﻓﻘﻲ ﺍﺳﺘﻔﺎﺩﻩ ﺷﻮﺩ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺳﺎﺧﺘﺎﺭ ﺗﻴﻢ ﭘﺮﻭژﻩ ‪BI‬‬
‫•‬
‫ﺩﺭ ﺳﺎﺧﺖ ﻳﻚ ﺳﻴﺴﺘﻢ ﻣﺒﺘﻨﻲ ﺑﺮ ﻣﻌﻤﺎﺭﻱ ‪ BI‬ﺭﻭﻳﻜﺮﺩ ﻣﺒﺘﻨﻲ ﺑﺮﺗﻮﻟﻴﺪ ﺍﺟﺰﺍ ﺣﺎﻛﻢ ﺍﺳﺖ‪،‬‬
‫ﺩﻭ ﺗﻴﻢ ﺑﻄﻮﺭ ﻣﺠﺰﺍ ﺩﺭ ﺍﻳﻦ ﺭﺍﺑﻄﻪ ﻣﺸﻐﻮﻝ ﺑﻪ ﻓﻌﺎﻟﻴﺖ ﺍﻧﺪ‪:‬‬
‫‪53‬‬
‫•‬
‫ﺗ‪‬ﻴﻢ ﺳﺎﺯﻧﺪﻩ ﻫﺴﺘﻪ ﺍﺻﻠﻲ ﺳﻴﺴﺘﻢ )‪(Core‬‬
‫•‬
‫ﺗﻴﻢ ﻛﺎﺭﺑﺮﺩﻱ ﻧﻤﻮﺩﻥ ﻫﺴﺘﻪ ﺍﺻﻠﻲ )‪(Extended‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
‫ﺗﻴﻢ ﺳﺎﺯﻧﺪﻩ ﻫﺴﺘﻪ ﺍﺻﻠﻲ ﺳﺎﻣﺎﻧﻪ)‪(Core‬‬
‫•‬
‫ﺍﻋﻀﺎﻱ ﺛﺎﺑﺖ ﺍﻳﻦ ﺗﻴﻢ ‪:‬‬
‫•‬
‫•‬
‫•‬
‫•‬
‫‪54‬‬
‫ﻳﻚ ﻧﻔﺮ ﻣﺪﻳﺮ ﭘﺮﻭژﻩ‪،‬‬
‫ﻳﻚ ﻧﻔﺮ ﻧﻤﺎﻳﻨﺪﻩ ﺗﺠﺎﺭﻱ‪،‬‬
‫ﺗﺤﻠﻴﻠﮕﺮﺍﻥ ﺍﺯ ﻃﺮﻑ ﺑﺨﺶ ﺗﻜﻨﻮﻟﻮژﻱ ﺍﻃﻼﻋﺎﺕ‪،‬‬
‫ﻣﺘﺨﺼﺼﻴﻦ ﺍﺯ ﻃﺮﻑ ﺑﺨﺶ ﺗﻜﻨﻮﻟﻮﺯﻱ ﺍﻃﻼﻋﺎﺕ ﻛﻪ ﻣﺘﺨﺼﺺ ﺩﺭ ﺍﻣﺮ ﺑﺮﻧﺎﻣﻪ ﻧﻮﻳﺴﻲ ﻭ‬
‫ﺗﺠﺰﻳﻪ ﺗﺤﻠﻴﻞ ﺳﻴﺴﺘﻢ ﺑﺎﺷﺪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﺗﻴﻢ ﻛﺎﺭﺑﺮﺩﻱ ﻧﻤﻮﺩﻥ ﻫﺴﺘﻪ ﺍﺻﻠﻲ )‪(Extended‬‬
‫•‬
‫‪55‬‬
‫ﻧﻘﺶ ﺍﺻﻠﻲ ﺩﺭ ﺭﺍﻫﺒﺮﻱ ﻣﺮﺍﺣﻞ ﭘﺮﻭژﻩ ﺭﺍ ﻧﺪﺍﺭﻧﺪ‪ ،‬ﺍﻋﻀﺎﻱ ﺍﻳﻦ ﺗﻴﻢ ﺩﺍﺭﺍﻱ ﺗﺨﺼﺺ ﻫﺎﻱ‬
‫ﻣﺨﺘﻠﻔﻲ ﻫﺴﺘﻨﺪ ﻭ ﺩﺭ ﻫﺮ ﻳﻚ ﺍﺯ ﻣﺮﺍﺣﻞ ﺍﻧﺠﺎﻡ ﭘﺮﻭژﻩ ﭼﻨﺎﻧﭽﻪ ﺑﻪ ﺗﺨﺼﺺ ﺁﻧﻬﺎ ﻧﻴﺎﺯ ﺑﺎﺷﺪ‪ ،‬ﺍﺯ‬
‫ﺍﻳﺸﺎﻥ ﺑﺮﺍﻱ ﺷﺮﻛﺖ ﺩﺭ ﺟﻠﺴﺎﺕ‪ ،‬ﺩﻋﻮﺕ ﺑﻪ ﻋﻤﻞ ﻣﻲ ﺁﻳﺪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﺳﺮﻭﻳﺲ ﺩﻫﻨﺪﻩ ﻫﺎﻱ ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮ ﺧﻂ‬
‫•‬
‫ﺳﺮﻭﻳﺲﺩﻫﻨﺪﻩ ﻫﺎﻱ ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮ ﺧﻂ ﻛﻪ ﺩﺭ ﻻﻳﻪ ﻣﻴﺎﻧﻲ ﻣﻌﻤﺎﺭﻱ ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ‬
‫ﺗﺤﻠﻴﻠﻲ ﻗﺮﺍﺭ ﺩﺍﺭﻧﺪ‪ ،‬ﺳﻪ ﻧﻮﻉ ﻫﺴﺘﻨﺪ‪:‬‬
‫•‬
‫•‬
‫•‬
‫‪56‬‬
‫‪) ROLAP‬ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮﺧﻂ ﺭﺍﺑﻄﻪﺍﻱ( ‪Relational OLAP‬‬
‫‪) MOLAP‬ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮﺧﻂ ﭼﻨﺪﺑﻌﺪﻱ( ‪Multi-dimensional OLAP‬‬
‫‪) HOLAP‬ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮﺧﻂ ﺗﺮﻛﻴﺒﻲ( ‪Hybrid OLAP‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫‪ROLAP‬‬
‫•‬
‫ﻳﻚ ﺳﺮﻭﻳﺲﺩﻫﻨﺪﻩ ‪ ،ROLAP‬ﺍﺯ ﻧﻮﻉ ﺗﻮﺳﻌﻪ ﻳﺎﻓﺘﻪﺍﻱ ﺍﺯ ﺳﻴﺴﺘﻢﻫﺎﻱ ﻣﺪﻳﺮﻳﺖ ﭘﺎﻳﮕﺎﻩﻫﺎﻱ ﺩﺍﺩﻩ ﺭﺍﺑﻄﻪﺍﻱ ﺍﺳﺘﻔﺎﺩﻩ‬
‫ﻣﻲﻛﻨﺪ‪.‬‬
‫•‬
‫ﭘﺮﺩﺍﺯﺵ ﺗﺤﻠﻴﻠﻲ ﺑﺮ ﺧﻂ ﺭﺍﺑﻄﻪ ﺍﻱ ﺑﺮﺍﺳﺎﺱ ﻧﻮﻉ ﺍﺭﺗﺒﺎﻁ ﺟﺪﻭﻝ ﻭﺍﻗﻌﻴﺖ ﺑﺎ ﺟﺪﺍﻭﻝ ﺑﻌﺪ ﺑﻪ ﺍﺷﻜﺎﻝ ﻣﺨﺘﻠﻔﻲ ﻣﺪﻝ‬
‫ﻣﻲﺷﻮﻧﺪ‪.‬‬
‫•‬
‫ﺍﻳﻦ ﺳﺮﻭﻳﺲ ﺩﻫﻨﺪﻩ‪ ،‬ﺳﺎﺧﺘﺎﺭﻫﺎﻱ ﺷﺎﻣﻞ ﺟﺪﺍﻭﻝ ﻭﺍﻗﻌﻴﺖ ﻭ ﺟﺪﺍﻭﻝ ﺑﻌﺪ ﺭﺍ ﺑﺎ ﺍﺳﺘﻔﺎﺩﻩ ﺍﺯ ﺟﺪﺍﻭﻝ ﻭ ﺭﺍﺑﻄﻪ ﻫﺎﻱ ﺑﻴﻦ‬
‫ﺍﻧﻬﺎ ﭘﻴﺎﺩﻩ ﺳﺎﺯﻱ ﻣﻲ ﻛﻨﺪ‪.‬‬
‫•‬
‫ﺩﺭ ﻭﺍﻗﻊ ‪ ،ROLAP‬ﻋﻤﻠﻴﺎﺕ ‪ OLAP‬ﺑﺮ ﺭﻭﻱ ﺩﺍﺩﻩﻫﺎﻱ ﭼﻨﺪﺑﻌﺪﻱ ﺭﺍ ﺑﻪ ﻋﻤﻠﻴﺎﺕ ﺭﺍﺑﻄﻪﺍﻱ ﺍﺳﺘﺎﻧﺪﺍﺭﺩ ﻭ ﺩﺳﺘﻮﺭﺍﺕ‬
‫‪ SQL‬ﻧﮕﺎﺷﺖ ﻣﻲﻛﻨﺪ‪.‬‬
‫‪57‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫‪MOLAP‬‬
‫•‬
‫ﺳﺮﻭﻳﺲﺩﻫﻨﺪﻩ ‪MOLAP‬ﺩﻳﺪﮔﺎﻩ ﭼﻨﺪ ﺑﻌﺪﻱ ﺍﺯ ﺩﺍﺩﻩ ﺭﺍ ﻣﺴﺘﻘﻴﻤﺎ ﺑﻪ ﺳﺎﺧﺘﺎﺭﻫﺎﻱ ﺁﺭﺍﻳﻪﺍﻱ‬
‫ﻧﮕﺎﺷﺖ ﻣﻲﻧﻤﺎﻳﺪ‪.‬‬
‫•‬
‫ﻳﻚ ﭘﺎﻳﮕﺎﻩ ﺩﺍﺩﻩ ﺗﺤﻠﻴﻠﻲ ﭼﻨﺪﺑﻌﺪﻱ ﺩﺍﺩﻩ ﺭﺍ ﺑﻪ ﺷﻜﻞ ﻳﻚ ﻣﻜﻌﺐ ﺩﺍﺩﻩ ﻣﻲﺑﻴﻨﺪ‬
‫‪58‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫‪HOLAP‬‬
‫•‬
‫•‬
‫‪59‬‬
‫‪ HOLAP‬ﻧﻴﺰ ‪ ROLAP‬ﻭ ‪ MOLAP‬ﺭﺍ ﺑﺎﻳﻜﺪﻳﮕﺮ ﺗﺮﻛﻴﺐ ﻣﻲﻛﻨﺪ‪.‬‬
‫ﺑﻪ ﻋﻨﻮﺍﻥ ﻣﺜﺎﻝ ﺍﺯ ‪ ROLAP‬ﺑﺮﺍﻱ ﺩﺍﺩﻩﻫﺎﻱ ﻣﺮﺑﻮﻁ ﺑﻪ ﺳﺎﺑﻘﻪ ﻭ ﺗﺎﺭﻳﺨﭽﻪ ﺍﺳﺘﻔﺎﺩﻩ‬
‫ﻣﻲﺷﻮﺩ‪ ،‬ﺩﺭ ﺣﺎﻟﻲ ﻛﻪ‪ ،‬ﺩﺍﺩﻩﻫﺎﻳﻲ ﻛﻪ ﺑﻪ ﺗﻨﺎﻭﺏ ﻣﻮﺭﺩ ﺩﺳﺘﺮﺳﻲ ﻫﺴﺘﻨﺪ‪ ،‬ﺩﺭ ﻳﻚ‬
‫‪ MOLAP‬ﺟﺪﺍﮔﺎﻧﻪ ﻧﮕﻬﺪﺍﺭﻱ ﻣﻲﺷﻮﻧﺪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﺑﺎﺯﮔﺸﺖ‬
‫ﻣﺰﺍﻳﺎ ﻭ ﻣﻌﺎﻳﺐ ﺳﺮﻭﻳﺲ ﺩﻫﻨﺪﻩ ﻫﺎﻱ ‪OLAP‬‬
‫‪60‬‬
‫•‬
‫ﻣﺰﺍﻳﺎ ﻭ ﻣﻌﺎﻳﺐ‪ : ROLAP‬ﺑﺮﺍﻱ ﻣﺠﻤﻮﻋﻪ ﺩﺍﺩﻩ ﻫﺎﻱ ﺑﺰﺭگ ﻣﻨﺎﺳﺐ ﺗﺮ ﻫﺴﺘﻨﺪ ﺯﻳﺮﺍ ﺩﺭ ﺻﻮﺭﺕ‬
‫ﻭﺟﻮﺩ ﭘﺮﺍﻛﻨﺪﮔﻲ ﺩﺭ ﺩﺍﺩﻩ‪ ،‬ﻣﺠﻤﻮﻋﻪ ﺩﺍﺩﻩ ﻫﺎﻱ ﭘﺮﺍﻛﻨﺪﻩ ﺩﺭ ﺟﺪﻭﻝ ﻫﺎ ﻓﺸﺮﺩﻩ ﺗﺮ ﺍﺯ ﺁﺭﺍﻳﻪ ﻫﺎ ﺫﺧﻴﺮﻩ‬
‫ﻣﻲ ﺷﻮﻧﺪ‪.‬‬
‫•‬
‫ﻣﺰﺍﻳﺎ ﻭ ﻣﻌﺎﻳﺐ‪ : MOLAP‬ﺯﻣﺎﻧﻲ ﻛﻪ ﺩﺍﺩﻩ ﻫﺎ ﭘﺮﺍﻛﻨﺪﻩ ﺑﺎﺷﻨﺪ ﺑﺎ ﻣﺸﻜﻞ ﻛﻤﺒﻮﺩ ﺣﺎﻓﻈﻪ ﺭﻭﺑﺮﻭ ﻣﻲ‬
‫ﺷﻮﺩ‪ .‬ﻭﻟﻲ ﺩﺭ ﻣﻮﺭﺩ ﻣﺠﻤﻮﻋﻪ ﺩﺍﺩﻩ ﻫﺎﻱ ﻛﻮﭼﻚ ﻛﻪ ﭘﺮﺍﻛﻨﺪﮔﻲ ﺩﺭ ﺍﻧﻬﺎ ﻛﻤﺘﺮ ﺍﺳﺖ‪ ،‬ﺳﺮﻋﺖ ﺑﺎﺯﻳﺎﺑﻲ‬
‫ﺩﺭ ‪ MOLAP‬ﺑﻴﺸﺘﺮ ﻣﻲ ﺑﺎﺷﺪ‪ .‬ﺍﺯ ﻃﺮﻑ ﺩﻳﮕﺮ ﺍﻳﻦ ﻧﻮﻉ ﺳﺮﻭﻳﺲ ﺩﻫﻨﺪﻩ ﻫﺎ ﺑﻪ ﺩﻳﺪﮔﺎﻩ ﺫﻫﻨﻲ ﻛﺎﺭﺑﺮ‬
‫ﻧﺰﺩﻳﻚ ﺗﺮ ﻫﺴﺘﻨﺪ‪.‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓﺮﻭﺷﻨﺪﮔﺎﻥ ﻣﺤﺼﻮﻻﺕ ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
Actuate
•
،Qlik Tech
•
IBM Cognos
•
،SAP Business Objects
•
Information Builders
•
SAP
•
،Microsoft
•
،Microstrategy
•
،Oracle
•
Panaroma Software
•
،SAS Institute
•
TIBCO Spotfire
•
،‫ﻫﻭﺵ ﺗﺟﺎﺭی‬
‫ﮔﺭﻭﻩ ﻓﺭﻓﺎ‬
61
‫ ﺩﺭ ﺑﺎﺯﺍﺭ‬BI ‫ﻣﻮﻗﻌﻴﺖ ﻓﺮﻭﺷﻨﺪﮔﺎﻥ‬
:‫• ﭘﻴﺸﺮﻭﺍﻥ ﺑﺎﺯﺍﺭ‬
SAS ‫ ﻭ‬Oracle ، SAP Business Objects ،IBM Cognos •
:‫• ﺗﻌﻘﻴﺐ ﻛﻨﻨﺪﮔﺎﻥ‬
‫ ﻭ‬Microsoft ،MicroStrategy ،Information Builders ،SAP •
Actuate
:‫• ﻣﺪﻋﻴﺎﻥ‬
QlikTech‫ ﻭ‬Panaroma Software •
‫ ﮔﺮﻭﻩ‬،‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
62
‫ﻓﺮﻓﺎ‬
‫ﻣﺮﺍﺟﻊ‬
•
•
•
•
Larissa T. Moss, “Improving Data Quality: Why is it so difficult?”
•
•
•
A Presentation on BI: “Enterprise Information Systems”
•
•
•
Fosca Giannotti, Dino Pedreschi, “Tecniche di Data Mining”, http://www-kdd.cnuce.cnr.it/
“Data Warehousing/Business Intelligence”, Available in www.eforceglobal.com
Paul Balacky & Richard Fayers, “A Presentation on Business Intelligence“, June 10th 2003
A Presentation on BI: “Business Intelligence: Data Warehousing, Data Acquisition, Data Mining, Business
Analytics, and isualization”
A Presentation on BI:”ETL”, www.ds.uillinois.edu
Chun Wei Choo, “Knowledge Management and The Knowing Organization”, Faculty of Information Studies,
University of Toronto, http://choo.fis.utoronto.ca
Ora Fish, “Data Warehousing: Changing Campus Culture ”, Rensselaer Polytechnic Institute
Dr. Silke Schoenert, “Knowledge Management and Project Management” , University of Koblenz-Landau,
Germany, schoen@uni-Koblenz
‫ﻓهﺮﺳﺖ‬
‫ ﮔﺮﻭﻩ‬،‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‬
‫ﻓﺮﻓﺎ‬
63
‫ﻣﺮﺍﺟﻊ ﺍﺩﺍﻣﻪ‬
‫•‬
‫ﮔﻠﺴﺘﺎﻧﯽ‪ ،‬ﺍﻣﻴﻦ‪ ،‬ﻫﻮﺵ ﺗﺠﺎﺭی ﻭ ﺗﺼﻤﻴﻤﺎﺕ ﮐﻼﻥ ﺳﺎﺯﻣﺎﻧﯽ‪ ،‬ﻣﺎﻫﻨﺎﻣﻪ ﺗﺪﺑﻴﺮ‪ ،‬ﺷﻤﺎﺭﻩ ‪.۱۹۰‬‬
‫•‬
‫‪"«،‬ﻫﻮﺵ ﺗﺠﺎﺭی« ﺿﺮﻭﺭﺕ ﺑﻨﮕﺎﻩﺩﺍﺭی ﺍﻗﺘﺼﺎﺩی"‪،‬ﺭﻭﺯﻧﺎﻣﻪ‬‫ﻓﻨﺎﻭﺭﺍﻥ‪www.vista.ir/article/347468/%C2%AB%D9%87%D9%88%D8%B4-‬‬
‫‪%D8%AA%D8%AC%D8%A7%D8%B1%DB%8C%C2%BB-%D8%B6%D8%B1%D9%88%D8%B1%D8%AA‬‬‫‪%D8%A8%D9%86%DA%AF%D8%A7%D9%87%E2%80%8C%D8%AF%D8%A7%D8%B1%DB%8C‬‬‫‪ ،%D8%A7%D9%82%D8%AA%D8%B5%D8%A7%D8%AF%DB%8C‬ﺳﻪ ﺷﻨﺒﻪ ‪ 19‬ﺁﺫﺭ ‪.1392‬‬
‫•‬
‫ﻣﺤﻘﺮ ﻋﻠﯽ ﺣﺴﻴﻨﯽ ﻓﺮﯾﺪ ﻋﻠﯽ ﻣﻨﺸﯽ ﺁﺻﻒ‪"،‬ﮐﺎﺭﺑﺮﺩ ﻫﻮﺵ ﺗﺠﺎﺭی ﺑﻪ ﻋﻨﻮﺍﻥ ﯾﮏ ﺗﮑﻨﻮﻟﻮژی ﺍﻁﻼﻋﺎﺕ ﺍﺳﺘﺮﺍﺗﮋﯾﮏ ﺩﺭ‬
‫ﺑﺎﻧﮑﺪﺍﺭی‪:‬ﺑﺎﺯﺭﺳﯽ ﻭ ﮐﺸﻒ ﺗﻘﻠﺐ"‪،‬ﻧﺸﺮﯾﻪ ﻣﺪﯾﺮﯾﺖ ﻓﻨﺎﻭﺭی ﺍﻁﻼﻋﺎﺕ‪ ،‬ﺩﻭﺭﻩ ﯾﮏ‪ ،‬ﺷﻤﺎﺭﻩ ﯾﮏ‪ ،‬ﭘﺎﯾﻴﺰ ﻭ ﺯﻣﺴﺘﺎﻥ ‪-105 ،1387‬‬
‫‪.120‬‬
‫‪64‬‬
‫ﻫﻮﺵ ﺗﺠﺎﺭﻱ‪ ،‬ﮔﺮﻭﻩ‬
‫ﻓﺮﻓﺎ‬
‫ﻓهﺮﺳﺖ‬
Download