Реферат тақырыбы: The conceptual, logical and physical data models


Characteristics of a Logical data model



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Characteristics of a Logical data model

  • Describes data needs for a single project but could integrate with other logical data models based on the scope of the project.

  • Designed and developed independently from the DBMS.

  • Data attributes will have datatypes with exact precisions and length.

  • Normalization processes to the model is applied typically till 3NF.

Physical Data Model
Physical Data Model describes a database-specific implementation of the data model. It offers database abstraction and helps generate the schema. This is because of the richness of meta-data offered by a Physical Data Model. The physical data model also helps in visualizing database structure by replicating database column keys, constraints, indexes, triggers, and other RDBMS features.


Characteristics of a physical data model:

  • The physical data model describes data need for a single project or application though it maybe integrated with other physical data models based on project scope.

  • Data Model contains relationships between tables that which addresses cardinality and nullability of the relationships.

  • Developed for a specific version of a DBMS, location, data storage or technology to be used in the project.

  • Columns should have exact datatypes, lengths assigned and default values.

  • Primary and Foreign keys, views, indexes, access profiles, and authorizations, etc. are defined.

Advantages and Disadvantages of Data Model:
Advantages of Data model:



  • The main goal of a designing data model is to make certain that data objects offered by the functional team are represented accurately.

  • The data model should be detailed enough to be used for building the physical database.

  • The information in the data model can be used for defining the relationship between tables, primary and foreign keys, and stored procedures.

  • Data Model helps business to communicate the within and across organizations.

  • Data model helps to documents data mappings in ETL process

  • Help to recognize correct sources of data to populate the model



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