Key elements of Data Wahrehousing

Tuesday, January 26, 2010

Overview
• A multi-dimensional database is created from fact and dimension tables to form objects called dimensions and cubes

Dimensions
•Dimensions are most often made up of several hierarchies
•Examples: time, geography, employee

Hierarchy
• Logical entity by which a business user might want to analyze fact data
• Each hierarchy can have one or more levels
Example: A hierarchy in the geography dimension –Country, State, County, City

Completely Balanced Hierarchy
• All leaf(end) nodes would be an equal level from the top level.
• E.g. : Geography dimension

Unbalanced Hierarchy
• Hierarchy in dimensions having an unbalanced distribution of leaf nodes relative to the top level.
E.g : Organization chart

Ragged Hierarchy
• Some hierarchies are typically balanced but are missing a unique characteristic of some members in a level.
• Example: geography hierarchy that contains the levels Country, State, and City. (USA-Washington-Seattle, Greece-Athens)

Cubes
• The cube is a multi dimensional data structure which we can query for business information.
• Each block of the cube is called a cell and is uniquely identified by a member in each dimension.
• Cubes reduce the query response time for the information worker to extract knowledge from the data – contain precalculated summary data called aggregations
• That is, cubes not only store multi dimensional data from fact tables, but also aggregations of that data.
(summing of sales figures up from stores level, to district level, to regional level)