Importance Of Data Warehousing

766 Words2 Pages

Concept hierarchies organize data or concepts in hierarchical forms or in certain partial order, these are used for expressing knowledge in concise, high-Ieve1 terms, and facilitating mining knowledge at multiple levels of abstraction. Concept hierarchies are also utilized to form dimensions in multidimensional databases and thus are essential components for data warehousing as well. In areas other than data mining, concept hierarchy is commonly called taxonomy. We adopt the term concept hierarchy because of its popularity in the community of data mining and knowledge discovery.
Concept Hierarchy in Data Warehousing:
While operational databases maintain state information, data warehouses typically maintain historical information. Although there are several forms of schema, e.g., star schema and snowflake schema, in the design of a data warehouse, the fact tables and dimension tables are its essential components. Users typically view the fact tables as multidimensional data cubes. The attributes of a dimension table may be organized as one or more concept hierarchies.
The use of concept hierarchies in a data warehousing system provides the foundation of operations roll-up and drill-down. To improve the …show more content…

Upon recognizing the importance of concept hierarchies, they proposed algorithms for mining generalized association rules, in which concept hierarchies are used for mining association rules and interesting rule detections. Interestingness is an important measure to determine the value of the discovered knowledge. In the complexity of a concept hierarchy is defined in terms of the number of its interior nodes, and the depth and height of each of these interior nodes. This complexity is then used to measure the interestingness of the discovered knowledge

Open Document