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Data Warehouse. Week 8 Introduction of Data Warehouse Multidimensional Analysis: OLAP. Data Warehouse. Integrated, Subject-Oriented, Time-Variant, Nonvolatile database that provides support for decision making. Characteristics of Data Warehouse. Integrated Centralized - PowerPoint PPT Presentation


  • Fox MISSpring 2011Data WarehouseWeek 8Introduction of Data WarehouseMultidimensional Analysis: OLAP

  • Data WarehouseIntegrated, Subject-Oriented, Time-Variant, Nonvolatile database that provides support for decision making

  • Characteristics of Data WarehouseIntegratedCentralizedHolds data retrieved from entire organizationTime Variant Flow of data through timeProjected dataNon-Volatile Data never removedAlways growing Subject-Oriented Optimized to give answers to diverse questionsUsed by all functional areas

  • Multidimensional Analysis:

    OLAP (Online Analytical Processing)

  • Advanced data analysis environmentSupports decision making, business modeling, and operations research activities

    Characteristics of OLAPUse multidimensional data analysis techniquesProvide advanced database supportProvide easy-to-use end-user interfacesSupport client/server architectureOnline Analytical Processing (OLAP)

  • Example: Sales

  • Multidimensional View of SalesMultidimensional analysis involves viewing data simultaneously categorized along potentially many dimensions

  • OLAP Server with Multidimensional Data Store Arrangement

  • Simple OLAP

  • Slice and Dice

  • Pivoting

  • OLAB Cube Example

  • OLAP Screen Example

  • OLAP Screen Example

  • Data Warehouse Modeling: Star SchemaData-modeling technique Also called star-join schema, data cube, or multi-dimensional schemaThe simplest style of data warehouse schema. The star schema consists of one or more fact tables referencing any number of dimension tablesMaps multidimensional decision support into relational databaseYield model for multidimensional data analysis while preserving relational structure of operational DB

    FactsThe fact table holds the main data. It includes a large amount of aggregated data, such as price and units soldDimensionsDimension tables, which are usually smaller than fact tables, include the attributes that describe the facts.Attributes

  • Star Schema for Sales

  • Data Warehouse Implementation Road Map