Even if it is another type of database (multidimensional, columnar, or some other proprietary database), you need to understand the specifics of that DBMS in order to implement the model.įred A. Quite often, it is a relational database, and you will have to understand how the tables, columns, data types, and the relationships between tables and columns are implemented in the specific relational database product. Implementing the physical data model requires understanding the characteristics and performance constraints of the database system being used. This model should be used to validate whether the resulting applications that are built fulfill business and data requirements. The logical model is used as a bridge from the application designer’s view to the database design and the developer’s specifications. ĭefinitions of the primary keys, foreign keys, alternate keys, and inversion entities.Identification of the business rules and relationships between those entities and attributes. Specific entities and attributes to be implemented. įeatures independent of specific database and data storage structures.The characteristics of the logical data model include:
It uses indexes and foreign keys to represent data relationships, but these are defined in a generic database context independent of any specific DBMS product. Like the conceptual data model, the logical data model is independent of specific database and data storage structures. As opposed to a conceptual data model, which may have very general terms, the logical data model is the first step in designing and building out the architecture of the applications. The business rules are appropriated into the logical data model, where they form relationships between the various data objects and entities. It includes a further level of detail, supporting both the business system-related and data requirements. It builds upon the requirements provided by the business group. The logical data model is the one used most in designing BI applications. Names, data types, and characteristics of entities and their attributes. īusiness terms and measures across different business units and those that are agreed upon for enterprise-wide usage.The conceptual data model is a tool for business and IT to define: For example, it allows business people to view sales data, expense data, customers, and products-business subjects that are in the integrated model and outside of the applications themselves. This model’s perspective is independent of any underlying business applications. This model focuses on identifying the data used in the business but not its processing flow or physical characteristics. The conceptual data model is a structured business view of the data required to support business processes, record business events, and track related performance measures. Application developers use the physical data model to design, build, and test application systems. The database design for operational and transactional systems is derived from ER logical data models while BI-related databases use logical dimensional models. Then database administrators and application developers will convert the logical data model into the tables, columns, keys, and other physical entities of a database. The logical data model is used as the blueprint of what data is involved while the physical data models detail how that data will be implemented. The physical data model makes up the third tier. 2.īI or analytical applications such as DW, data marts, and OLAP cubes. Transactional or operation applications such as enterprise resource planning (ERP) systems. The logical data model is the architect or designer view of the data.
It helps us understand the details of the data, but not how it is implemented.
The logical data model is the next layer down, and is the one we are most involved in when designing the BI application.
0 kommentar(er)
