More Related Content
Similar to Data Models - Department of Computer Science & Engineering (20)
More from acemindia (13)
Recently uploaded (20)
Data Models - Department of Computer Science & Engineering
- 1. Data Models Department of Computer Science & Engineering
- 2. Objectives Why data models are important? About the basic data-modeling building blocks. How the major data models evolved? How data models can be classified by level of abstraction? 2
- 3. The Importance of Data Models Data models Relatively simple representations, usually graphical, of complex real-world data structures. Facilitate interaction among the designer, the application programmer, and the end user End-users have different views and needs for data Data model organizes data for various users 3
- 4. Data Model Basic Building Blocks Entity - anything about which data are to be collected and stored. Attribute - a characteristic of an entity. Relationship - describes an association among entities One-to-many (1:M) relationship Many-to-many (M:N or M:M) relationship One-to-one (1:1) relationship Constraint - a restriction placed on the data. 4
- 5. The Evolution of Data Models Hierarchical Network Relational Entity relationship Object oriented (OO) 5
- 6. The Hierarchical Model Developed in the 1960s to manage large amounts of data for complex manufacturing projects 6
- 7. The Hierarchical Model The hierarchical structure contains levels, or segments Depicts a set of one-to-many (1:M) relationships between a parent and its children segments Each parent can have many children each child has only one parent 7
- 8. The Network Model Created to Represent complex data relationships more effectively Improve database performance Impose a database standard Schema Conceptual organization of entire database as viewed by the database administrator 8
- 9. The Network Model (continued) Subschema Defines database portion seen by the application programs that actually produce the desired information from data contained within the database Data Management Language (DML) Defines the environment in which data can be managed 9
- 10. The Network Model (continued) Schema Data Definition Language (DDL) Enables database administrator to define schema components Subschema DDL Allows application programs to define database components that will be used DML Works with the data in the database 10
- 11. The Network Model (continued) 11
- 12. The Relational Model Developed by Codd (IBM) in 1970 Considered ingenious but impractical in 1970 Conceptually simple Computers lacked power to implement the relational model Today, microcomputers can run sophisticated relational database software 12
- 13. The Relational Model (continued) Relational Database Management System (RDBMS) Performs same basic functions provided by hierarchical and network DBMS systems, in addition to a host of other functions Most important advantage of the RDBMS is its ability to hide the complexities of the relational model from the user 13
- 14. The Relational Model (continued) Table (relations) Matrix consisting of a series of row/column intersections Related to each other through sharing a common entity characteristic Relational diagram Representation of relational databases entities, attributes within those entities, and relationships between those entities 14
- 15. The Relational Model (continued) Relational Table Stores a collection of related entities Resembles a file Relational table is purely logical structure How data are physically stored in the database is of no concern to the user or the designer This property became the source of a real database revolution 15
- 16. The Relational Model (continued) 16
- 17. The Relational Model (continued) Rise to dominance due in part to its powerful and flexible query language Structured Query Language (SQL) allows the user to specify what must be done without specifying how it must be done SQL-based relational database application involves: User interface A set of tables stored in the database SQL engine 17
- 18. The Entity Relationship Model Widely accepted and adapted graphical tool for data modeling Introduced by Chen in 1976 Graphical representation of entities and their relationships in a database structure 18
- 19. The Entity Relationship Model (continued) Entity relationship diagram (ERD) Uses graphic representations to model database components Entity is mapped to a relational table Entity instance (or occurrence) is row in table Entity set is collection of like entities Connectivity labels types of relationships Diamond connected to related entities through a relationship line 19
- 20. The Entity Relationship Model 20
- 21. The Entity Relationship Model 21
- 22. The Object Oriented Model Modeled both data and their relationships in a single structure known as an object Object-oriented data model (OODM) is the basis for the object-oriented database management system (OODBMS) OODM is said to be a semantic data model 22
- 23. The Object Oriented Model (continued) Object described by its factual content Like relational models entity Includes information about relationships between facts within object, and relationships with other objects Unlike relational models entity Object becomes basic building block for autonomous structures 23
- 24. The Object Oriented Model (continued) Object is an abstraction of a real-world entity Attributes describe the properties of an object Objects that share similar characteristics are grouped in classes Classes are organized in a class hierarchy Inheritance is the ability of an object within the class hierarchy to inherit the attributes and methods of classes above it 24
- 25. The Object Oriented Model (continued) 25
- 26. Data Models: A Summary 26
- 27. Degrees of Data Abstraction Way of classifying data models Many processes begin at high level of abstraction and proceed to an ever-increasing level of detail Designing a usable database follows the same basic process 27
- 28. Degrees of Data Abstraction (continued) American National Standards Institute (ANSI) Standards Planning and Requirements Committee (SPARC) Defined a framework for data modeling based on degrees of data abstraction(1970s): External Conceptual Internal 28
- 29. Degrees of Data Abstraction 29
- 30. 30 Thank you