Designing conceptual models of data warehouses is the next stage which should be implemented after the phase determination of measure and dimension . At this stage, created a model that can describe any data or tables that will be stored in a data warehouse, the following connectedness among others.
The data or tables in the data warehouse can be modeled by using modeling tools such as ER diagram , star schema , Snowflake schema , or FCO-IM ( Fully Communication Oriented Information Modelling ). But in general, are tools used star schema or Snowflake schema .
The star schema is the simplest style of data warehouse schema. The star schema consists of a few fact tables (possibly only one) referencing any number of dimension tables.
Star schema will describe the fact table , the table that represents the measure , as a “data center”. This table will be connected with the tables that describe the dimensions to measurethe ( dimension table ). For example, the star schema for data warehouse sale is:
Snowflake schema architecture is a more complex variation of a star schema design. The main difference is that dimensional tables in a snowflake schema are normalized. one or more of the existing hierarchy in the dimension tables are normalized (decomposition) into several smaller table, so they have a typical relational database design.