Dimensional Modelling (DM) is a data structure technique that is specifically designed for data storage in a data warehouse. The goal of dimensional modelling is to optimise the database so that data can be retrieved more quickly. In a data warehouse, a dimensional model is used to read, summarise, and analyse numeric data such as values, balances, counts, weights, and so on. Relation models, on the other hand, are designed for adding, modifying, and deleting data in a real-time Online Transaction System.

Following are the steps that should be followed while creating a dimensional model:

• Identifying the business process : The first step is to identify the specific business processes that a data warehouse should address. This might be Marketing, Sales, or Human Resources, depending on the organization's data ANALYTIC needs. The quality of data available for that process is also a factor in deciding which business process to use. It is the most crucial step in the Data Modeling process, and a failure here would result in a cascade of irreversible flaws.
• Identifying the grain : The level of detail for the business problem/solution is described by the grain. It's the procedure for DETERMINING the lowest level of data in any table in your data warehouse. If a table contains sales data for each day, the granularity should be daily. Monthly granularity is defined as a table that contains total sales data for each month.
• Identifying the dimension : Date, shop, inventory, and other nouns are EXAMPLES of DIMENSIONS. All of the data should be saved in these dimensions. The date dimension, for example, could include information such as the year, month, and weekday.
• Identifying the fact : This stage is linked to the system's business users because it is here that they gain access to data housed in the data warehouse. The majority of the rows in the fact table are numerical values such as PRICE or cost per unit.
• Building the schema : The Dimension Model is implemented in this step. The database structure is referred to as a schema (arrangement of tables).