What is Dimensional Modeling?

Dimensional modeling is a logical design method that follows to present the data in a standard structure that is perceptive and enables high-performance access. It is genetically dimensional and observes to a discipline that needs the relational model with several restrictions.

Each dimensional model is composed of one table with a multipart key, known as the fact table, and a group of smaller tables known as dimension tables. Each dimension table has an individual element primary key that correlates to one of the elements of the multipart key in the fact table. This distinctive star-like structure is known as star join. This defines dates back to the initial days of relational databases.

A fact table, because it has a multipart primary key made up of two or more foreign keys continually defines a many-to-many relationship. The general fact tables also include one or more mathematical facts that appear for the merger of keys that represent each record.

The general facts in a fact table are numeric and additive. Additivity is essential because data warehouse applications never fetch an individual fact table record. Because they fetch back hundreds, thousands, of these data at a time, and the only beneficial thing to do with several records is to insert them up.

Dimension tables include descriptive textual data. The dimension attributes are the source of the interesting constraints in data warehouse queries and are the source of the row headers in the Structured Query Language (SQL) answer set.

The master entity-relationship diagram can have Sales Calls, Order Entry, Shipment Invoices, User Payments, and Product Returns, etc. In a method, the entity-relationship diagram does itself a disservice by representing on one diagram multiple processes that never coexist in a single data set at a single consistent point in time.

Therefore the first step in modifying an entity-relationship diagram to a group of dimensional modeling diagrams is to separate the entity-relationship diagram into its discrete business procedure and to model each one independently.

The second step is to choose those many-to-many relationships in the entity-relationship model including mathematical and additive non-key facts and label them as fact tables.

The third step is to denormalize some remaining tables into flat tables with single element keys that are linked directly to the fact tables. These tables become dimension tables. In cases where a dimension table connects to more than one fact table, we represent this same dimension table in both schemas, and it defines the dimension tables as “conformed” between the two-dimensional models.