Dimensional modeling is a data structure technique that has been deployed for data storage in a data
warehouse. The model helps the database managers retrieve data quickly from a database. The
dimensional model in the data warehouse can assist in summarizing, reading, and analyzing balances,
counts, weights, and values.
Steps in Dimensional Modeling
The SQL server dimensional modeling follows a systematic approach to develop or establish the model.
Applying the model to a data warehouse involves the following steps.
- The business process has been identified initially, and the following stages are planned
- The second stage is identifying the grain, which involves the detailing level.
- In the next step, the database operators should identify the dimensions.
- The fourth stage is the identification of facts.
- Export ERD
- The final stage is all about building stars.
In the following section, you can find these steps in detail. Learning them in detail will help you
understand the model clearly and implement it in your database model.
1. Business Process Identification
A data warehouse needs to work according to the requirements of a business. Therefore, it is essential
to evaluate the business process in the beginning. Depending on the business process, the data analysis
requirements will be considered.
2. Grain Identification
Grain refers to the level of problem that a business faces. Nevertheless, it also evaluates the essential
solutions for tackling the problems. Grain identification is the most crucial stage of a SQL server dimensional modeling process.
3. Dimension Identification
The dimension identification stage is also helpful for data storage and inventory management.
Dimension identification is the process of determining and identifying the data storage spaces. Keeping
data in the right place will make the database systematic and logical.
4. Fact Identification
The fourth stage is fact identification, which deals with facts to understand the data accessibility
requirements. The data must be stored according to the accessibility requirements depending on many
factors. Keeping accessibility in mind will help in seamless data access with precision.
5. Schema Building
The final stage of dimensional modeling is schema building to organize data in a systematic manner.
Schema building will assist in an effortless data sorting from the extensive database. As a result, the
relevance of the sorted data will increase significantly.
So, these are the fundamental stages of developing a dimensional database model for a data
warehouse. You can visit SqlDBM to learn more in this regard and gain information on SQL programming
and database management. The web portal comes with rich information for database enthusiasts and