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Business datasets (overview, structure, naming conventions, business rules) Expand / Collapse
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Posted Monday, January 28, 2013 3:55 AM
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Hi Guys

I was wondering if someone could point me in the right direction.
I need to gather information about different datasets used in different business areas: banking, insurances, online betting, sales, CRM ETC.
So in summary: Is there anything that I could read to understand how other businesses (I’m currently in healthcare) do their business intelligence and analytics. How does the business works? How do their facts and dimensions look like? What kind of business rules do they apply?

Do you know anything that I could read: books, articles, papers?
It would be nice to get top level information first so I would prefer few hundred pages rather than few thousands for starters.
Thanks for your help in advance

Mike
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Posted Friday, February 08, 2013 9:06 AM


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michal.giczewski (1/28/2013)
I was wondering if someone could point me in the right direction.
I need to gather information about different datasets used in different business areas: banking, insurances, online betting, sales, CRM ETC.
So in summary: Is there anything that I could read to understand how other businesses (I’m currently in healthcare) do their business intelligence and analytics. How does the business works? How do their facts and dimensions look like? What kind of business rules do they apply?


Oracle Business Intelligence Suite provides out of the box templates for different industries, a starting point would be http://docs.oracle.com/cd/E10415_01/doc/index.htm

Having said that, in my opinion it takes a lot of time - depending on previous experience and operational knowledge of a particular industry, to understand how it works.


_____________________________________
Pablo (Paul) Berzukov

Author of Understanding Database Administration available at Amazon and other bookstores.

Disclaimer: Advice is provided to the best of my knowledge but no implicit or explicit warranties are provided. Since the advisor explicitly encourages testing any and all suggestions on a test non-production environment advisor should not held liable or responsible for any actions taken based on the given advice.
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