Data Warehouse Environment Architecture part-4 - ETL- iNFORMATICA DEVELOPER

Sunday, May 19, 2019

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Data Warehouse Environment Architecture part-4

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DWH Paradigm

  • Bill Inmon's paradigm: Data warehouse is one part of the overall business intelligence system. An enterprise has one data warehouse, and data marts source their information from the data warehouse. In the data warehouse, information is stored in 3rd normal form.                                      
  • Ralph Kimball's paradigm: Data warehouse is the conglomerate of all data marts within the enterprise. Information is always stored in the dimensional model.
          
 There is no right or wrong between these two ideas, as they represent different data warehousing philosophies. In reality, the data warehouse in most enterprises are closer to Ralph Kimball's idea. This is because most data warehouses started out as a departmental effort, and hence they originated as a data mart. Only when more data marts are built later do they evolve into a data warehouse.


Data Warehouse Environment Architecture



ODS Vs Datawarehouse
   Operational Data Store
  Data Warehouse



Characteristics:
Data Focused Integration
From Transaction Processing Focused Systems
Subject Oriented
Integrated
Non-Volatile
Time Variant
Age Of The Data:
Current, Near Term
(Today, Last Week’s)
Historic
(Last Month, Qtrly, Five Years)
Primary Use:
Day-To-Day Decisions
Tactical Reporting
Current Operational Results
Long-Term Decisions
Strategic Reporting
Trend Detection
Frequency Of Load:
Twice Daily , Daily, Weekly
Weekly, Monthly, Quarterly


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