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Outline Data Models Categories of Data Models History of Data Models Schema Three- Schema Architecture DBMS Component DBMS Architecture 5. Data Models. Data Model A set of concepts to describe the structure of a database, and certain constraints that the database should obey. Data Model Operations Operations for specifying database retrievals and updates by referring to the concepts of the data model. Operations on the data model may include basic operations and user- defined operations. Categories of data models. Conceptual (high- level, semantic) data models Provide concepts that are close to the way many users perceive data. Such as entity, attribute, relationship among entities (will explain more detail in ER model) Physical (low- level, internal) data models Provide concepts that describe details of how data is stored in the computer. Ex. Tree, Graph, dsb Implementation (representational) data models Provide concepts that fall between the above two, balancing user views with some computer storage details. Such as relational, network or hierarchical data model 7. History of Data Models Network Model the first one to be implemented by Honeywell in 1. IDS System). Adopted heavily due to the support by CODASYL (CODASYL - DBTG report of 1. Later implemented in a large variety of systems - IDMS (Cullinet - now CA), DMS 1. Unisys), IMAGE (H. P.), VAX - DBMS (Digital Equipment Corp.). Elmasri/Navathe, Fundamentals of Database Systems, Fourth Edition Unary Relational Operations (cont.) zPROJECT Operation. Fundamentals of Database Systems, Fourth Edition Unary Relational Operations (cont.) zRename Operation. Fundamentals of Database Systems, 4th Edition-TOC draft 3. Chapter 2 Database System Concepts and Architecture. Fundamentals of Database Systems, 4th Edition-TOC draft 5. Elmasri and Navathe, Fundamentals of Database Systems. Fundamentals of Database Systems, Fourth Edition - Idea. Fundamentals of Database Systems Fourth Edition El Masri -. Data in a Network in terms of Interdependencies and Connections Among Data Items Graphs Hierarchical Data Model implemented in a joint effort by IBM and North American Rockwell around 1. Resulted in the IMS family of systems. The most popular model. Other system based on this model System 2k (SAS inc.) Data in Hierarchies in terms of Interdependencies and Connections Among Data Items Tree 8. History of Data Models. Relational Model proposed in 1. E. F. Codd (IBM), first commercial system in 1. Now in several commercial products (DB2, ORACLE, SQL Server, SYBASE, INFORMIX). Object- oriented Data Model(s) several models have been proposed for implementing in a database system. One set comprises models of persistent O- O Programming Languages such as C (e. OBJECTSTORE or VERSANT), and Smalltalk (e. GEMSTONE). Additionally, systems like O2, ORION (at MCC - then ITASCA), IRIS (at H. P.- used in Open OODB). History of Data Models. Object- Relational Models Most Recent Trend. Started with Informix Universal Server. Exemplified in the latest versions of Oracle- 1. DB2, and SQL Server etc. See the following examples 1. Hierarchical Graphical Representation 1. Fundamentals of database systems fourth edition.pdf. Fundamentals of Azure. Handle System Proxy Server. fundamentals of database systems fourth edition. . Fundamentals of Database Systems (4th Edition) (9780321122261) by Elmasri. This fourth edition expands on many of the most popular database. Fundamentals of Database Systems combines clear explanations of theory. 1/2 Fundamentals Of Database Systems Fourth Edition Fundamentals Of Database Systems Fourth Edition PDF Download Fundamentals Of Database Systems. Liebert Ds System Design Manual Senior Clerk Exam Question Paper With. Fundamentals of database systems / Ramez Elmasri. and database system implementation tech-. There are significant organizational changes in the sixth edition. Fundamentals of Database Systems 4th Ed.zip download at 2shared. compressed file Fundamentals of Database Systems 4th Ed.zip download at www. Fundamentals of Database Systems 4th Edition Solution Manual.zip download at. Network Graphical Representation 1. Relational Model. Relational Model of Data Based on the Concept of a Relation Relation - a Mathematical Concept Based on Sets Strength of the Relational Approach to Data Management Comes From the Formal Foundation Provided by the Theory of Relations RELATION A Table of Values A Relation May Be Thought of as a Set of Rows A Relation May Alternately be Though of as a Set of Columns Each Row of the Relation May Be Given an Identifier Each Column Typically is Called by its Column Name or Column Header or Attribute Name 1. Relational Tables - Rows/Columns/Tuples 1. Entity Relationship (ER) Data Model. Originally Proposed by P. Chen, ACM TODS, Vol. No. 1, March. 19. Conceptual Modeling of Database Requirements Allows an Application's Information to be Characterized Basic Building Blocks are Entities and Relationships Well- Understood and Studied Technique Well- Suited for Relational Database Development Did Not Originally Include Inheritance!! ER Diagram 1. 6Object- Oriented Database Models/Systems. Reasons for Creation of Object Oriented Databases Need for More Complex Applications Need for Additional Data Modeling Features Increased Use of Object- oriented Programming Languages Experimental Systems Orion at MCC, IRIS at H- P Labs, Open- oodb at T. I., ODE at ATT Bell Labs, Postgres - Montage - Illustra at UC/B, Encore/observer at Brown Commercial OO Database Products Ontos, Gemstone ( - gt Ardent), Objectivity, Objectstore ( - gt Excelon), Versant, Poet, Jasmine (Fujitsu GM) Also - Relational Products with Object Capabilities 1. Object- Oriented Database Models/Systems. OO Databases Try to Maintain a Direct Correspondence Between Real- world and DB Objects Object have State (Value) and Behavior (Operations) In OO Databases Objects May Have an Object Structure of Arbitrary Complexity in Order to Contain All of the Necessary Information That Describes the Object In Traditional Database Systems Information About a Complex Object is Often Scattered Over Many Relations or Records Leads to Loss of Direct Correspondence Between a Real- world Object and Its Database Representation Supports OO Programming Concepts Inheritance, Polymorphism, etc. Object- Oriented Database Declarations. Specifying the Object Types Employee, Date, and Department Using Type Constructors 1. Object- Oriented Database Declarations. Adding Operations to Definitions of Employee and Department 2. Schemas. Database Schema The description of a database. Includes descriptions of the database structure and the constraints that should hold on the database. Schema Diagram A diagrammatic display of (some aspects of) a database schema. Schema Construct A component of the schema or an object within the schema, e. STUDENT, COURSE. Database State/Snapshot The actual data stored in a database at a particular moment in time. Also called the current set of occurrences/instances). Schema diagram 2. Database Schema Vs. Database State. Database State Refers to the content of a database at a moment in time. Initial Database State Refers to the database when it is loaded Valid State A state that satisfies the structure and constraints of the database. Distinction The database schema changes very infrequently. The database state changes every time the database is updated. Schema is also called intension, whereas state is called extension. Three- Schema Architecture. Proposed to support DBMS characteristics of Program- data independence. Support of multiple views of the data. The three- schema architecture 2. Another view Three Schema Architecture 2. Three- Schema Architecture. Defines DBMS schemas at three levels Internal schema at the internal level to describe physical storage structures and access paths. Typically uses a physical data model. Conceptual schema at the conceptual level to describe the structure and constraints for the whole database for a community of users. Uses a conceptual or an implementation data model. External schemas at the external level to describe the various user views. Usually uses the same data model as the conceptual level. Conceptual Schema. Describes the Meaning of Data in the Universe of Discourse Emphasizes on General, Conceptually Relevant, and Often Time Invariant Structural Aspects of the Universe of Discourse Excludes the Physical Organization and Access Aspects of the Data 2. External Schema. Describes Parts of the Information in the Conceptual Schema in a form Convenient to a Particular User Groups View Derived from the Conceptual Schema 2. Internal Schema. Describes How the Information Described in the Conceptual Schema is Physically Represented in a Database to Provide the Overall Best Performance 3. Unified Example of Three Schemas 3. Data Independence. Ability that Allows Application Programs Not Being Affected by Changes in Irrelevant Parts of the Conceptual Data Representation, Data Storage Structure and Data Access Methods Invisibility (Transparency) of the Details of Entire Database Organization, Storage Structure and Access Strategy to the Users Both Logical and Physical Recall Software Engineering Concepts Abstraction the Details of an Application's Components Can Be Hidden, Providing a Broad Perspective on the Design Representation Independence Changes Can Be Made to the Implementation that have No Impact on the Interface and Its Users 3. Data Independence. Logical Data Independence The capacity to change the conceptual schema without having to change the external schemas and their application programs. Physical Data Independence The capacity to change the internal schema without having to change the conceptual schema. Data Independence. When a schema at a lower level is changed, only the mappings between this schema and higher- level schemas need to be changed in a DBMS that fully supports data independence. The higher- level schemas themselves are unchanged. Hence, the application programs need not be changed since they refer to the external schemas. Physical Data Independence 3. Logical Data Independence 3. DBMS Languages. Data Definition Language (DDL) Used by the DBA and database designers to specify the conceptual schema and internal schema of a database and any mapping between the two. In many DBMSs where a clear separation of conceptual and internal schema, DDL is used to define conceptual schema only. Storage definition language (SDL) define the internal schema and view definition language (VDL) are used to define user view and their mapping to the conceptual schemas. |
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