Levels of Data Modeling PDF

202 Levels of Data Modeling Data modeling is typically divided into three main levels: Conceptual Logical Physical. Conceptual Data Modeling A conceptual data model offers a high-level overview of the data structure. *** *** *...

202 Levels of Data Modeling Data modeling is typically divided into three main levels: Conceptual Logical Physical. Conceptual Data Modeling A conceptual data model offers a high-level overview of the data structure. *** *** * * It focuses on identifying the main entities and relationships in the system without diving * ** ** ** ** into details like attributes, data types, or constraints. ~~ ~~ ~~ ~~ ~~ ~~ ~~ ~~ * This model is often used in discussions with stakeholders to ensure the data requirements * ** ** ** align with business goals. ** * ** Key Features: ** Represents core entities (actual objects) and their relationships. *** *** *** *** Does not include detailed attributes or data types. *** *** ~~ ~~ ~~ ~~ Is technology-independent, focusing purely on business concepts. ** Example: For an e-commerce platform, a conceptual model might include entities like ** *** *** * * *** Customer, *** *** Order, and *** *** Product, *** with relationships like * * * "( customer ) places ( order )" ` ` ** ** ` ` * ( Customer to Order ) ** ` ` ` ` ** and Product to Order. *** ` ` ` ` *** (TODO Annotate) Logical Data Modeling A logical data model provides ** ** * * * a more Detailed Structure, ** ** * * defining Entities, ** *** *** Attributes, *** * and Relationships. ** *** It introduces *** Data Types *** and Relationships *** *** (e.g., One-To-Many, ** ** ** Many-To-Many) ** *** but remains independent of any specific database technology. ** ~~ ~~ * This level is more detailed than the conceptual model and is used to lay out the full scope of * ** data requirements. ** * ** Key Features: ** * Defines attributes for each entity ** ** and their data types ** ** (e.g., text , number ). ` ` ` ` * * Specifies primary and foreign keys to establish relationships. ** ** ** ** * * Includes data normalization to minimize redundancy and ensure data integrity. ** ** ~~ ~~ * * Is technology-agnostic, focusing on data structure rather than database ** ** ~~ implementation. ~~ * ** Example: In a logical model for the e-commerce example, ** * * the Customer entity might have attributes like CustomerID , Name , and Email. ` ` * * ` ` ` ` ` ` ` Order table can contain customerID and ProductID as a foreign key, establishing the ` ` ` ` ` * ** relationship of the order table with Customer and Product table. ** ` ` ` ` * * Physical Data Modeling * The physical data model is the final stage, where the logical data model is Transformed To * * * * * ** Fit The Constraints Of A Specific Database Management System (DBMS). ** * * This model details how data will be stored physically, including ** ** * ** Indexing, ** ** Storage, ** and Access Methods. ** ** * It is optimized for performance and is specific to the chosen DBMS. ** ** * ** Key Features: ** * Implements Specific Data Types based on the DBMS ** *** (e.g., VARCHAR, ** **  ** INT ** * in SQL). * * Considers * ** Indexing ** and Partitioning ** ** * for optimized performance. * * Maps relationships to Actual Database Constructs ** ** ** *** (e.g., Tables, ** ** ** Columns, ** ** Foreign Keys). ** * Includes detailed storage information, like ** ** * ** File Structures ** and Disk Allocation.** ** ** Example: For the e-commerce example, ** the Customer entity would now be implemented as a Customer Table in SQL, ` ` ` ` *** *** * with Specific Data Types such as VARCHAR(255) for Name and Email ** ** ` ` ` ` ` ` * * and Indexing on CustomerID to speed up queries. ** ** ` ` *  ⭐ Summary Table: Levels of Data Modeling ~ Model Level ~ ~ Description ~ ~ Detail Level ~ ~ Example ~ ** Conceptual Model** *** High-level overview ** Low ** Entities: Customer , ** ` ` focusing on Entities ** ** ` Order , Product ` ` ` and Relationships ** *** ** Logical Model ** * Detailed structure Medium ** Attributes: ** with Entities, ** ** ` CustomerID , Name , ` ` ` ** Attributes, and** ` Email ` ** Relationships *** ** Physical Model ** *** Database-specific *** High *** * Specific Table ** implementation with ** Structures and ** ** Data Types and ** ** Indexing *** ** Storage Details ***