Logical Dimensional Data Models
Logical data models address the following areas of interest:
1. Validating application models against business requirements
2. Creating requirements for physical data models and database design
3. Identifying business entities and the relationships between the entities
Logical data models create a single view of all data. You can create a logical data model to address performance, consistency, and redundancies in your data. You use the logical data model to create a physical data model that accesses the data.
Physical Dimensional Data Models
Keep in mind the following considerations when you create a physical data model:
1. How scalable is your design? How scalable is the physical database management system (DBMS)?
2. What queries, ETL processes, and other applications does the data warehouse require?
3. Is there an abstracted data model that you can use to improve performance?
4. How will you operate or maintain the data warehouse?
Logical data models address the following areas of interest:
1. Validating application models against business requirements
2. Creating requirements for physical data models and database design
3. Identifying business entities and the relationships between the entities
Logical data models create a single view of all data. You can create a logical data model to address performance, consistency, and redundancies in your data. You use the logical data model to create a physical data model that accesses the data.
Physical Dimensional Data Models
Keep in mind the following considerations when you create a physical data model:
1. How scalable is your design? How scalable is the physical database management system (DBMS)?
2. What queries, ETL processes, and other applications does the data warehouse require?
3. Is there an abstracted data model that you can use to improve performance?
4. How will you operate or maintain the data warehouse?
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