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Shilpa Seth.  Multidimensional Data Model Concepts Multidimensional Data Model Concepts  Data Cube Data Cube  Data warehouse Schemas Data warehouse.

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Presentation on theme: "Shilpa Seth.  Multidimensional Data Model Concepts Multidimensional Data Model Concepts  Data Cube Data Cube  Data warehouse Schemas Data warehouse."— Presentation transcript:

1 Shilpa Seth

2  Multidimensional Data Model Concepts Multidimensional Data Model Concepts  Data Cube Data Cube  Data warehouse Schemas Data warehouse Schemas - Star SchemaStar Schema - Snowflake SchemaSnowflake Schema - Fact Constellation SchemaFact Constellation Schema

3 MULTIDIMENSIONAL DATA MODELS MULTIDIMENSIONAL DATA MODELS A data warehouse is based on a multidimensional data model which views data in the form of a Data Cube. A data cube, such as sales, allows data to be modeled and viewed in multiple dimensions. Dimension tables, such as time (month, quarter, year) Fact table contains measures (such as units, price) and keys to each of the related dimension tables.

4 Sales volume as a function of product, month, and region. Brand Region Year Product Country Quarter Type State Month Week City Day Product Store Time Dimensions: Product, Store, Time Hierarchical summarization paths

5 Dimensions and Facts Dimensions are entities or perspective with respect to which an organization wants to keep records. Facts are numerical measures. Back

6 ∑ Product milk eggs. cheese Time(months ) 2345 Multidimensional view of sales data Store Toronto Vancouver Victoria ∑ ∑ ∑ ∑ ∑ ∑

7 In data warehousing literature, an n-D base cube is called a Base cuboid. The top most 0-D cuboid, which holds the highest-level of summarization, is called the Apex cuboid. The lattice of cuboids forms a Data Cube. Cube: A Lattice of Cuboids

8 all product store time product, store product, time store, time product, store, time 0-D(apex) cuboid 1-D cuboids 2-D cuboids 3-D(base) cuboid Back

9 Star Schema Snowflake Schema Fact Constellation Schema

10 Sales fact Product Store City Time

11 Measures – Units, Price. Dimensions – Product, Time, Store.

12 A single, large and central fact table and one table for each dimension. Every fact points to one tuple in each of the dimensions and has additional attributes. Star Schema makes heavy use of denormalization to optimize for speed, at a potential cost of storage space.

13 Store Key Product Key Time Key Units Price Store Dimension Time Dimension Product Dimension Sales Fact Table Store Key City State Country Region Time Key Year Quarter Month Product Key Brand Product Type Measures Back

14 Variant of star schema model. A single, large and central fact table and one or more tables for each dimension. Dimension tables are normalized i.e. split dimension table data into additional tables.

15 Store Key Product Key Time Key Units Price Time Dimension Product Dimension Sales Fact Table Store Key region City Key Time Key Year Quarter Month Product Key Brand Product Type City Key City Street City Dimension Store Dimension Back

16 Multiple fact tables share dimension tables. This schema is viewed as collection of stars hence called galaxy schema or fact constellation. Sophisticated application requires such schema.

17 Time Key Year Quarter Month Store Key Product Key Time Key Units Price Store Dimension Product Dimension Sales Fact Table Store Key City Country State Region Product Key Brand Product Type Shipper Key Store Key Time Key Units Price Shipping Fact Table Time Dimension Shipper Key Shipper Name Shipper type Shipper Back

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