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Data Warehouse Architectures

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Data Warehouse Architectures Data Warehouse Architectures Presentation Transcript

  • Data Warehouse Architectures
    • Data warehouses and their architectures vary depending upon the specifics of an organization's situation. Three common architectures are:
    • Data Warehouse Architecture (Basic)
    • Data Warehouse Architecture (with a Staging Area)
    • Data Warehouse Architecture (with a Staging Area and Data Marts)
    Types
    • End users directly access data derived from several source systems through the data warehouse.
    Data Warehouse Architecture (Basic)
  •  
    • The figure illustrates three things:
    • Data Sources (operational systems and files)
    • Warehouse (metadata, summary data, and raw data)
    • Users (analysis, reporting, and mining)
    Data Warehouse Architecture (Basic)
    • You need to clean and process your operational data before putting it into the warehouse. You can do this programmatically, although most data warehouses use a staging area instead. A staging area simplifies building summaries and general warehouse management.
    • Staging area - A place where data is processed before entering the warehouse.
    Data Warehouse Architecture (with a Staging Area)
  •  
    • This illustrates four things:
    • Data Sources (operational systems and files)
    • Staging Area (where data sources go before the warehouse)
    • Warehouse (metadata, summary data, and raw data)
    • Users (analysis, reporting, and mining)
    Data Warehouse Architecture (with a Staging Area)
    • To customize your warehouse's architecture for different groups within your organization.
    • This by adding data marts , which are systems designed for a particular line of business.
    • The following example illustrates an example where purchasing, sales, and inventories are separated. In this example, a financial analyst might want to analyze historical data for purchases and sales.
    Data Warehouse Architecture (with a Staging Area and Data Marts)
  •  
    • This illustrates five things:
    • Data Sources (operational systems and flat files)
    • Staging Area (where data sources go before the warehouse)
    • Warehouse (metadata, summary data, and raw data)
    • Data Marts (purchasing, sales, and inventory)
    • Users (analysis, reporting, and mining)
    Data Warehouse Architecture (with a Staging Area and Data Marts)
    • Data Marts – A data mart is a focused subset of a data warehouse that deals with a single area of data and is organized for quick analysis.
    • Flat files - Flat files are data files that contain records with no structured relationships unlike relational database
    • Meta Data – Information about the data
    • Data stores – Data Sources
    Appendix