What are the techniques of Dimensional Modeling?

Data MiningDatabaseData Structure

Fact Tables and Dimension Tables − The element of dimensional modeling is that nearly every type of business data can be described as a type of cube of data, where the cells of the cube include measured values and the edges of the cube represent the natural dimensions of the data.

It can enable more than three dimensions in the designs, therefore it technically must call the cube a hypercube, although the method cube and data cube are used by essentially everyone.

Facts − A dimensional model characterizes facts and attributes. A fact is generally something that is not recognized in advance. A fact is a view in the marketplace. Several facts in the business world are mathematical, although a few can be text-valued.

The designer must suspect that some mathematical data field, specifically if the value is a floating-point number, is possibly a fact, not an attribute. Sometimes a mathematical value such as “standard cost” appears to be an attribute of the product dimension, and it appears to be a constant that is popular in advance.

Attributes − Attributes are generally text fields, and they generally define a characteristic of a tangible thing. The most apparent attributes are the definitions of products. The flavor of a product is a famous attribute of the product, and it is possibly shown in an outstanding way on the product packaging.

Dimensions − The textual attributes that define things are organized inside the dimensions. In a retail database, at the lowest, it can have a product dimension, a store dimension, a customer dimension, a promotion dimension, and a time dimension.

A dimension is a set of text-like attributes that are largely applied to each other. There is an amount of designer judgment in the choice of dimensions. In a retail database, it keeps tries to integrate the product dimension with the store dimension and create an individual massive product-store dimension.

If it can have 1000 products and 100 stores, it should ask how many product-stores it is ended up with when it is tried to combine these dimensions. If there was no significant correlation between product and store, and each product was sold in each store, then our combined product-store dimension will be the Cartesian product of the two initial dimensions, and it can have 100,000 product-stores.

In a dimensional model, the attributes in the dimension tables play an essential role. These attributes are textual, or they act like text, they take on discrete values, and they are the source of software constraints and row headers in the last report.

Updated on 09-Feb-2022 13:13:09