Data Model |
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Data Model Relational model In Relational model data is normalized to 1st, 2nd or 3rd Normal form. 1s Normal form 1NF, each column must contain only a single value and each row must contain the same columns. 2nd Normal form A relation must first fulfill the requirements to be in First Normal Form. Additionally, each nonkey attribute in the relation must be functionally dependent upon the primary key. 2NF attempts to reduce the amount of redundant data in a table by extracting it, placing it in new table(s) and creating relationships between those tables. 3rd Normal form A relation must first fulfill the requirements to be in Second Normal Form. Additionally, all attributes that are not dependent upon the primary key must be eliminated An example of a 2NF table that fails to meet the requirements of 3NF is:
In order to express the same facts without violating 3NF, it is necessary to split the table into two:
Dimensional model In dimensional model data is denormalized. The typical design is that of a Star where their is a central fact table containing additive, measurable facts and this central fact table is in relationship with dimensional tables which generally contain text filters that normally occurs in the WHERE clause of a query. The dimensional model is often implemented on top of the relational model using a star schema, consisting of one table containing the facts and surrounding tables containing the dimensions. The Star schema consists of a few "fact tables" (possibly only one, justifying the name) referencing any number of "dimension tables".the star schema's dimensions are denormalized with each dimension being represented by a single table The snowflake schema is represented by centralized fact tables which are connected to multiple dimensions. In the snowflake schema, however, dimensions are normalized into multiple related tables When the dimensions of a snowflake schema are elaborate, having multiple levels of relationships, and where child tables have multiple parent tables. what are the advantages and disadvantages of a star schema and snowflake schema. In Star schema In Star schema fact table is in normalized format and dimention table is in denormalized format keeping queries simple and providing fast response time In snowflake schema In snowsflake both fact and dimention tables are in normalized format will reduse the query performance because more joins is there savings small storage spaces |
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